Podcast appearances and mentions of Simon Johnson

What should the government be doing to get us AI ready? How do we make sure people co-exist with AI and aren't just replaced by it? What role should trade unions have? What are 'tech towns' and how important are they in the AI race? Nobel prize winning economist Simon Johnson is back to tell us about his role as the chair of the government's AI Institute which will use workplace data shared by over thirty major corporations to track, in real-time, how AI adoption is shifting job availability, wage growth, and macroeconomic productivity across the UK. The Rest is Money is brought to you by Octopus Energy, Britain's smart energy pioneer. Email: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠the⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠restismoney@goalhanger.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@TheRestIsMoney⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@TheRestIsMoney⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@RestIsMoney⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Advertise with us: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Partnerships@goalhanger.com⁠⁠ For more Goalhanger Podcasts, head to ⁠www.goalhanger.com⁠ Video Editor: Dylan Bonham Producer: Isabelle Bougeard Exec Producers: Chris Sawyer and Tom Whiter Learn more about your ad choices. Visit podcastchoices.com/adchoices

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president could still fire commissioners, as the Court now permits, but if those firings broke quorum, the agency would be unable to proceed until replacements were confirmed. The guardrail would

This week's video transcript summary is here. You can click on any bulleted section to see the actual transcript. Thanks to Granola for its software.There was an issue with this only going to paid subscribers, so sending it again. Apologies to those who get it twice. I appreciate being paid so feel free to upgrade if you enjoy TWTW.EditorialIntelligence: Who Owns it?This week the word “AI” feels too small.AI is a technology. Intelligence is its product. And if intelligence is the product, the question is no longer just: Which model is best? Who has the cheapest tokens? Who owns the weights? Who controls the data center? Those are important questions, but they are lower in the stack.The bigger question is simpler and more political:Who owns intelligence?That sounds abstract until you make it concrete. Intelligence is becoming something companies can capture, package, serve, meter, route, improve, and sell.It can write code, answer questions, design molecules, automate offices, run agents, draft legal work, advise scientists, serve consumers, and reshape workflows. It is not merely software. It is a general-purpose capability. And all humans could benefit from more of it.General-purpose capabilities have a habit of becoming public questions. But the default answer, that public good is best delivered by government, is the wrong answer in this context.The Product Is IntelligenceWe should stop talking about AI as a feature and start talking about intelligence as the universal thing that is delivered as an input to the world.Water is an input. Electricity is an input. Literacy is an input. Connectivity is an input. Once a society depends on them, access stops being optional. Nobody needs government to build every well, power plant, school, or network. But everybody understands that a civilization cannot be organized around less than universal and reliable access to foundational inputs.Intelligence is reaching that level of importance now that we all know it is real.Government should not own it, operate it, or develop it. Quite the opposite. Companies are the right actors to build fast, compete hard, improve models, serve customers, and discover the real use cases. Self-interest is a useful framing here. Markets are good at finding demand, reducing costs, and turning invention into services people actually use.Companies are the right operators, developers, and owners. But that does not settle the real question of who owns the benefits. That is an economic question.If intelligence becomes metered infrastructure, what happens to the value it creates?The Ownership StackThis week's articles keep circling the same issue from different directions but in the nature of ‘circling' never quite nail it.Jamin Ball's “Own Your Weights” starts with the enterprise version of the question. Owning a model file is not enough. The durable asset is the loop: the data flywheel, the evaluations, the reinforcement system, the workflow learning, and the operating context that lets capability compound.Benedict Evans' “Ways to Think About Token Pricing” adds the market layer. Tokens may become essential, abundant, and cheap, like mobile data. But being essential does not guarantee that the token layer captures the value. The money may move up the stack to whoever owns the workflow, the customer, the distribution, or the application.Alex Karp's fight with the labs, reported in “Alex Karp Is Saying What Every Angry CEO Is Thinking About AI”, is the same argument in sharper enterprise language. Companies are afraid that model providers will not just sell intelligence, but learn from customer workflows and then move into the markets where those workflows create value. The “All-in” group are echoing Karp's view.And “What Is Loop Engineering, and Who Owns It?” names the new contested terrain. The loop is where intelligence meets the world. Whoever owns the loop owns the learning. Whoever owns the learning owns the compounding asset.That is why “who owns intelligence?” is not a slogan. It is the question under the model layer, the application layer, the enterprise layer, and the economic layer.Because intelligence is the product, the tools creating it are fragmented and competitive. So there is no logic in trying to discuss this at the level of a single company or set of tools and models.The Old Promise Was That Commerce Would Tame PowerThe essays this week give the historical backdrop.Deirdre McCloskey, in “What Really Caused the Industrial Revolution”, argues that modern growth came not simply from capital accumulation, but from a change in permission: ordinary people were allowed to innovate, trade, build, and be honored for it.That matters because intelligence could be another expansion of permission. It could make more people capable of building, learning, creating, coding, researching, translating, selling, and coordinating. It could lower the cost of competence.But only if access is broad.Paul Krugman's “AI in an Age of Oligarchy” warns that the same technology lands differently in different political economies. A new general-purpose technology entering a broad, open, upwardly mobile society is one thing. The same technology entering a concentrated economy, with extreme wealth and weak counterweights, is another.Tim O'Reilly's Economist essay, “Elon Musk is building a form of capitalism that Adam Smith would hate”, makes the governance point more directly. The old liberal hope was that commerce would tame arbitrary power. Markets, boards, courts, shareholders, disclosure, and competition would discipline the prince.But what if the prince uses markets to escape discipline?Henry Farrell's “political economy of billionaire derangement” pushes the same point. Founder culture, monopoly ambition, peer rivalry, weak correction mechanisms, and vast private control can amplify appetites rather than restrain them.The danger with intelligence is not that companies build it. They should. Companies build it, meter it, use public tolerance and public infrastructure to scale it, learn from everyone who uses it. All of those things are inevitable and healthy. Market forces will sort out winners from losers. The real danger is that the winners treat all of the surplus produced as purely private.Metered Intelligence Creates SurplusIf metering is not the problem, what is?The problem is pretending that metered intelligence creates value only for the metering entity. Metering water is only tolerated as a public good. If the public were blackmailed by a private water company with the threat of no water we would all rebel.Once we understand that the product of AI is intelligence we can see that every time intelligence is used, there is the immediate transaction: the user pays, the provider serves.But there is also system value. Usage creates signals. Workflows reveal patterns. Prompts, corrections, failures, preferences, integrations, edge cases, and business processes all help define where intelligence is useful and how it should improve. Intelligence breeds intelligence.Even when customer data is contractually protected, the market learns. The platform learns where demand is. The product team learns which workflows matter. The ecosystem learns which jobs are vulnerable, which tasks are automatable, and which parts of the economy can be reorganized around machine intelligence.So the surplus is not born in a vacuum.It rests on public science, public education, public data exhaust, public law, public infrastructure, public energy systems, public tolerance for data centers, and billions of human interactions. It is served by companies, but it is not made only by companies.This is why “Americans Deserve a Dividend From AI Companies' Riches” belongs at the center of this week's issue. The detail can be debated. The principle is harder to dismiss. If intelligence becomes a new foundational resource, then some part of the wealth it creates should flow back to the people whose society makes it possible. Intelligence did not suddenly appear. AI is built on the entire history of human intelligence. It benefits from it and at the same time evolves it.Not Nationalization. A Human Wealth Fund.If intelligence belongs to everybody, some conclude that government ownership of intelligence is the right outcome.Governments are not well suited to build, operate, or improve intelligence. They will move too slowly, regulate too early, politicize the wrong things, and confuse economic participation with operational control.Andrew McAfee's “Why I Didn't Sign the AI Open Letter” is useful here. His objection is not that the technology is unimportant. It is that steering too hard before we understand the shape of the change can become its own failure mode. Marc Andreessen's satire of AI regulation is less policy than temperament, but it captures a real Silicon Valley fear: that regulation can become permission, capture, and incumbency before it becomes wisdom.That fear should be taken seriously.But it does not answer the economic question. It answers only the operational one.How can the economic benefits of intelligence be distributed? The better answer is a sovereign human wealth fund.Call it a sovereign wealth fund if you must, but the phrase is too national. Intelligence will not respect borders. The leading companies are global. The models, chips, data centers, agents, platforms, and workflows will be transnational from the beginning. If the value created by intelligence is global, then the mechanism for sharing some of that value should begin with the companies global enough to capture it. The nice thing about xAI, OpenAI, and Anthropic is that they are supranational.These companies own and operate intelligence. Let them compete. Let them profit. Let them keep the incentives that make the system improve. But if intelligence is the new water, the wealth it creates cannot belong only to the companies that meter it. And they, themselves, have the power to fix it, even more than governments.Access will become a Human Right; Ownership Is the Economic DesignThis is where human rights come in. There is no right to access an AI model, yet. But there will soon be a need to change that.Not as a claim that every person is entitled to every frontier model at every moment for free. That is not serious. Capacity has costs. Models have costs. Inference has costs. Data centers have costs. Although those costs will decline over time, possibly quite quickly as self-learning models address costs.The claim is more basic: in a world where intelligence becomes a primary input into education, work, health, science, citizenship, creativity, and economic agency, baseline access to intelligence starts to look like a civic requirement.That could mean public access layers. It could mean education credits. It could mean open models. It could mean AI dividends. It could mean public-interest compute. It could mean taxes on rents. It could mean a company-initiated human wealth fund that returns some of the upside to society without handing the operating system to the state. The latter could couple wealth growth with universal distribution of ownership.The exact mechanism matters. But the distinction matters more.Government should not own intelligence. It should be universally available. And people should have a claim on the wealth intelligence creates.The Frontier Is Also PhysicalThe abstraction is not weightless.“The Fight Against AI Data Centers Is Just Beginning”, “New York becomes the first state to enact a data center moratorium”, Reuters on pollution from Musk's xAI power project, and DataGravity's “Who Captures Value in AI Infrastructure?” all say the same thing from the ground up.Intelligence uses land. It uses power. It uses water. It uses chips. It uses grid capacity. It uses neighborhoods. It uses public patience.That makes the value question unavoidable. A society can accept the buildout if the buildout is legible as shared progress. It will resist it if the costs are local, the profits are private, and the benefits feel enclosed.Who Owns the “Loop”?The week ends where it began.“Anthropic and Blackstone” are betting that implementation is the next trillion-dollar business. “Vint Cerf” is working on identity for agents on the open internet. “GPT-Red” points toward systems that improve their own robustness. “Kimi K3” adds another open frontier model to the global mix.The model race continues. The deployment race is accelerating. The governance race is behind.My view is this:The central product of this era is intelligence. Companies have figured out how to capture it, package it, serve it, and meter it. That is good. It should stay in the hands of builders who have the incentive to make it better.But intelligence is too foundational to become just another private toll booth. A significant part of it will turn out to be free to users.As intelligence becomes a general-purpose resource, then access to it becomes a human-capability question, and the surplus from it becomes an economic-justice question. Not because government should run it. Because government should not run it. The operating layer belongs with companies. The wealth question belongs with everyone. But companies are best placed to turn that into a process of distribution.The question is not whether companies should build intelligence. They should.The question is whether humanity gets a stake in the wealth created by the thing that may soon become its most important shared input.Contents* Essays* Deirdre McCloskey on What Really Caused the Industrial Revolution* AI in an Age of Oligarchy* Elon Musk is building a form of capitalism that Adam Smith would hate* Murky Mirror: Truth and Consequences* The political economy of billionaire derangement* Is there any “oligarchy” to fight?* AI* Nearly 200 Economists and Tech Leaders Warn of A.I. Threats* Why I Didn't Sign the AI Open Letter* Own Your Weights* Ways to Think About Token Pricing* Alex Karp Is Saying What Every Angry CEO Is Thinking About AI* The AI Agents Are Coming for Microsoft Office* What Is Loop Engineering, and Who Owns It?* The Fight Against AI Data Centers Is Just Beginning* 6 months to live for open models* Americans Deserve a Dividend From AI Companies' Riches* Who Gets to Define the Frontier?* GPT-Red: Unlocking Self-Improvement for Robustness* Anthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just models* Vint Cerf is working on a plan to unleash AI agents on the open internet* xai-org/grok-build, now open source* The Pulse: What can we learn from Bun's rapid Rust rewrite with AI?* Orphan risks at the frontier of artificial intelligence* The Lab of the Future Should Feel Like a Data Center* Why AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”* Kimi K3 Tech Blog: Open Frontier Intelligence* Venture Capital* Three Years In* Venture Has Rarely Looked More Bifurcated* The Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active Now* Are Prediction Markets Doomed to Fail?* Regulation* Exclusive: The Next Frontier of the Deportation Wars: College Campuses* The Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.* India's crackdown on a new WhatsApp feature risks setting a global precedent* Let's build a children's public internet* Computer cops* Google is better at playing the AI regulations game* Infrastructure* Who Captures Value in AI Infrastructure?* New York becomes the first state to enact a data center moratorium* Pollution from Musk's unpermitted xAI power project hits hardest in Black communities* Interview of the Week* The End of the End of Geography* Startup of the Week* Radical AI's Joseph Krause: The Scientist Building The “Waymo” Lab For New Materials* Post of the Week* Marc Andreessen on AI RegulationEssaysDeirdre McCloskey on What Really Caused the Industrial RevolutionYascha Mounk and Deirdre McCloskey | Persuasion | July 11, 2026Yascha Mounk interviews Deirdre McCloskey about her argument that the modern world's economic liftoff came less from capital accumulation than from a change in ideas. McCloskey says both left and right versions of the conventional story rely too heavily on investment: the left stresses exploitation and surplus value, while the right stresses virtuous saving by capitalists. Her objection is historical and economic. Human beings had always invested, from irrigation works and Roman roads to seed grain, and simple accumulation quickly runs into diminishing returns.McCloskey's alternative is that northwestern Europe, first Holland, then Britain and Scotland, and then the North American colonies, developed a liberal ideology that changed who was allowed to innovate and be honored for it. The conversation links that shift to the erosion of inherited hierarchy, the spread of dignity for ordinary commercial life, and a moral vocabulary in which liberalism is not merely procedural but connected to virtues and values. The point is not that machines, coal, trade, and institutions did not matter, but that they do not explain the scale and timing of modern enrichment without a cultural permission structure for innovation.The interview also turns to the contemporary defense of liberalism. Mounk frames the series around the worry that liberalism is often treated as too thin to command allegiance, while its opponents speak more directly to moral passions. McCloskey's case is that liberal societies became rich because they dignified experimentation and ordinary enterprise, and that liberals need to recover the moral language behind that claim.Read moreAI in an Age of OligarchyPaul Krugman | Paul Krugman | July 12, 2026Paul Krugman frames AI as a major technological shock arriving inside an already unequal political economy. The post says AI's economic and social effects may take years to understand, but argues that the setting matters now: America has much greater wealth concentration and political inequality than it did in the 1950s and 1960s, when progressive taxation, stronger regulation, and more active antitrust might have contained some of the destructive effects of a new technology.Krugman's opening claim is that the same technology would likely have different consequences in a more level society. In today's United States, he writes, extreme wealth is both a cause and effect of policies that favor a small elite, including low effective taxes on capital and high incomes, weak enforcement of worker protections and antitrust, and cuts to programs that benefit ordinary Americans.The article is explicitly more about oligarchy than AI. Krugman says the paid sections document the rise of the “.0002%,” the economics and politics of extreme wealth, how oligarchy will shape AI's impact, and possible policy paths. His caveat is that AI itself may still produce a pushback against oligarchy, but absent that, he expects the pre-existing concentration of wealth and power to magnify AI's downsides.Read moreElon Musk is building a form of capitalism that Adam Smith would hateAuthor: Tim O'Reilly Published: July 12, 2026Tim O'Reilly argues that Elon Musk is using the legal forms of shareholder capitalism to escape the restraints that shareholder capitalism was supposed to impose. The article begins with SpaceX's public-market structure: ordinary public investors get little meaningful governance power, Musk keeps roughly 85 percent of the votes through super-voting shares, buyers waive jury trials and class actions, the company qualifies as controlled, and removal of Musk depends on the share class he controls. In O'Reilly's framing, that is not ordinary founder control; it is a design for being answerable to no one, possibly beyond Musk's own lifetime.The killer detail is the article's turn through Albert Hirschman, Montesquieu, James Steuart, Adam Smith, and Keynes. Older defenses of commerce held that markets would tame princely passions because the self-interest of merchants was safer than arbitrary rule. O'Reilly says Musk reverses that hope. The market discipline that was supposed to cage the prince has become the lever by which the prince raises capital, removes feedback loops, and carries private power into politics, government, Mars, robots, AI, or whatever ambition comes next.The pull is the link to AI governance. O'Reilly says corporations are already a kind of artificial intelligence: narrow-input systems that act at a scale no individual human can match. Their partial controls include independent boards, shareholder votes, courts, disclosure, regulators, public pressure, and activism. If the leaders building frontier AI strip those alignment mechanisms out of their own companies, the governance of the company becomes a preview of the governance of the machine.Read more: The EconomistMurky Mirror: Truth and ConsequencesAuthor: Esther Dyson Published: July 14, 2026Esther Dyson argues that today's institutional crisis is better viewed through the 14th century than through recent political history. Using Barbara Tuchman's A Distant Mirror as her frame, she compares a world of famine, plague, church schism, feudal predation, and purposeless war with a present in which institutions again feel brittle, incentives are badly aligned, and power is shifting into forms that are hard to govern.The killer detail is the historical analogy between land, corporations, and AI. Dyson moves from nobles who controlled serfs and territory, to the East India Company as a quasi-sovereign business, to today's AI systems and data centers as a possible new sector that crosses and weakens both nation-states and companies. The question is whether AI becomes a new kind of private land, owned by a new nobility, or an open prairie that many people can cultivate.The pull is human attention. Dyson says the central question is not what AI will do to people, but how people will react to it: whether they can value love, kindness, embodied attention, and artisanal human presence in a world of seductive artificial offerings.Read more: SourceThe political economy of billionaire derangementAuthor: Henry Farrell Published: July 15, 2026Henry Farrell argues that the visible political radicalization of some Silicon Valley billionaires is not a random personality quirk, but a product of the political economy that made them. Starting from Tyler Cowen's dismissal of “billionaire derangement syndrome” and Tim O'Reilly's warning that Elon Musk is using shareholder capitalism to escape shareholder restraint, Farrell flips the phrase: the question is why billionaires themselves can become deranged.The killer detail is Farrell's use of Peter Thiel as both theorist and example. Thiel's Stanford lectures described startups as monarchies and founders as figures vested with unusual power, while Silicon Valley culture rewarded eccentricity, monopoly ambition, and founder exceptionalism. Farrell says those ideas combined with dense founder-investor networks, peer rivalry, and weak correction mechanisms to amplify rather than discipline princely appetites.The pull is the ideological problem for classical liberals who once saw tech wealth as an ally of markets and freedom. Farrell says commerce did not tame the passions; in parts of Silicon Valley, the passions have begun to devour markets, institutions, and the liberal story that justified them.Read more: SourceIs there any “oligarchy” to fight?Matthew Yglesias | Slow Boring | July 16, 2026Matthew Yglesias argues that “oligarchy” is a rhetorically powerful but analytically loose way to describe American politics. The post begins from Bernie Sanders' “Fighting Oligarchy” tour, Amy Klobuchar's warning about a MAGA “broligarchy,” and the long afterlife of the Martin Gilens and Benjamin Page paper that was widely summarized as showing that only the rich matter in policy outcomes. Yglesias says the evidence supports a weaker claim: affluent people and business leaders have unusual access and influence, but that is not the same as rule by a small cabal.His main distinction is between inequality and oligarchy. The Gilens-Page measure treated the top 10 percent of households as “the wealthy,” and later critics found that rich and middle-class preferences usually align; in the cases where they differ, the rich win about 53 percent of the time. Yglesias also says business executives get special access partly because their decisions are materially important to communities, jobs, investment, and local tax bases, not only because of campaign donations.The post preserves Jerusalem Demsas' counterpoint from their podcast discussion: privileged donor and business access can still violate democratic equality even if the oligarchy label overstates the structure of power. Yglesias' narrower claim is that Democrats should be precise about what problem they are trying to solve, because donor influence can also push the party left on climate and cultural issues in ways that alienate many voters.Read more: Slow BoringAINearly 200 Economists and Tech Leaders Warn of A.I. ThreatsAuthor: Ben Casselman Published: July 13, 2026Ben Casselman reports on “We Must Act Now,” a statement warning that artificial intelligence could transform the economy faster than any previous technology and that policymakers need to move faster to understand and respond. The statement says AI may become radically more powerful over the next 10 years, bringing risks such as large-scale job displacement as well as opportunities such as higher living standards. Nearly 200 people signed, including 15 Nobel laureates, the chief economists of OpenAI and Anthropic, Anthropic co-founder Jack Clark, former Google CEO Eric Schmidt, and venture capitalist Vinod Khosla.The killer detail is who joined the warning. Casselman notes that the signatories include economists who have historically been skeptical of Silicon Valley's most dramatic AI job-loss forecasts, including Daron Acemoglu and Simon Johnson, the MIT professors who won the 2024 Nobel in economics. Erik Brynjolfsson, who helped organize the statement, says there has been a notable change in the profession and that economists and policymakers are not ready for the “tsunami” he sees coming.The pull is the measurement problem. The statement does not offer a specific policy menu, but calls for economists, policymakers, and industry leaders to understand the economics of transformative AI and steer it toward complementing humans. Brynjolfsson says one high priority is better data on AI's spread and impact, because current measures tell conflicting stories about job losses and which workers are most exposed.Read more: The New York TimesWhy I Didn't Sign the AI Open LetterAuthor: Andrew McAfee Published: July 13, 2026Andrew McAfee explains why he did not sign “We Must Act Now,” the AI economy statement organized in part by his longtime collaborator Erik Brynjolfsson. McAfee agrees with the letter's starting point that AI is likely to become radically more powerful over the next decade and that it is a general-purpose technology. His objection is not to urgency or to studying AI's economic effects, but to the framing of risk, displacement, and institutional steering as the first move.The killer detail is McAfee's line edit. He says the original letter comes close, then “bounces off the crossbar” by calling for incentives, guardrails, and institutions to steer AI before we know enough about its actual impacts. He points to mixed current evidence: labor-market canaries, but also rising software job postings, low unemployment for younger workers, rising real median income, and claims that AI-adopting companies are adding workers faster than low-adopting peers. His worry is that the letter leans toward upstream governance and dirigisme when the evidence may call for capability building instead.The pull is his replacement statement. McAfee keeps the three-paragraph structure but changes the emphasis: AI is likely to become radically more powerful; like earlier world-changing technologies it will raise living standards while also bringing harms and shocks; and economists, policymakers, and technology leaders should build the capabilities to respond quickly and effectively. It is a concise version of the permissionless-innovation case inside the AI policy debate.Read more: The Geek WayOwn Your WeightsAuthor: Jamin Ball Published: July 10, 2026Jamin Ball argues that the enterprise AI debate about whether companies should “own their weights” or rent models from frontier labs is asking too narrow a question. A model weight file gives a company control over a point-in-time artifact, but not durable control over the capability stack. In his framing, the weight file is a melting ice cube: it does not get worse in absolute terms, but it falls behind as frontier systems improve and enterprise needs change.The killer detail is what Ball says companies really need to own: the data flywheel, reinforcement learning infrastructure, and evaluation harness that produce and improve the model. Simply deploying an open-weights model and declaring sovereignty leaves the enterprise with yesterday's capability and no way to compound workflow-specific learning.The pull is that enterprise AI control may be less about model ownership than operating ownership. The defensible layer is the system that turns company data, edge cases, business definitions, and evaluations into continuously improving performance.Read more: Clouded JudgementWays to Think About Token PricingAuthor: Benedict Evans Published: July 9, 2026Benedict Evans argues that today's AI token prices are a temporary signal from a supply-constrained market, not a reliable guide to long-term value capture. The open question is whether foundation models keep durable pricing power or become commodity infrastructure as data-center capacity, inference efficiency, and model competition all shift. His current read is that the visible market dynamics point toward commoditization unless something materially changes.The killer detail is the mobile data analogy. Evans says cellular networks became a trillion-dollar industry with hundreds of billions in capex after data usage exploded, but carrier stocks went nowhere because value moved up the stack. Tokens may behave similarly: an opaque unit tied to marginal cost, sold through bundles, essential to everything, yet not necessarily where profits accrue.The pull is uncertainty, not prediction. Evans lists paths to model dominance, including network effects, less competition, regulation, export controls, or a lab pulling ahead on execution, but says each requires a new fact not yet visible. Without that change, the model layer looks more like infrastructure beneath the products that capture value.Read more: SourceAlex Karp Is Saying What Every Angry CEO Is Thinking About AIAuthor: Tim Higgins Published: July 11, 2026Tim Higgins reports that Palantir CEO Alex Karp has turned corporate frustration with AI labs into a public argument about enterprise control. Palantir released a white paper, “Institutional Sovereignty in the Age of AI,” laying out steps companies and governments can take to protect themselves from OpenAI, Anthropic, and other foundation-model providers. The article links that paper to Karp's CNBC appearance, where he said “something has gone completely wrong” in the relationship between AI labs and customers and argued that enterprises are paying for tokens that create little value.The killer detail is the value-capture question. Higgins writes that Karp's critique has resonated because AI labs may gain power and insight from customer data, workflows, and decision-making, even when enterprise policies say customer data are not used for training. David Sacks amplified the concern by arguing that Anthropic is moving from the model layer into vertical applications such as science, security, legal, and coding, raising the fear that model providers will watch where value is being created and then move into those markets directly.The pull is that Karp is not alone, even if his style is unusually combative. Higgins notes that Satya Nadella has also warned that companies need to retain the learnings created when they use AI models, while Mark Zuckerberg has framed Meta's new model release partly around lower-cost frontier intelligence. The article presents Karp's campaign as one sign that established technology companies and large enterprises are trying to define where they fit when AI labs become central infrastructure, application competitors, and potential IPO giants at the same time.Read more: The Wall Street JournalThe AI Agents Are Coming for Microsoft OfficeAlex Wilhelm | Cautious Optimism | July 11, 2026Alex Wilhelm argues that one of the week's quieter AI questions is whether the productivity market that Microsoft successfully moved into subscription software is now being attacked by agentic tools. The piece begins with the infrastructure backdrop: SK Hynix raised $26.5 billion in a U.S. listing while building U.S. HBM and advanced-packaging capacity, and memory, chip, and foundry companies are now priced for sustained AI demand.Wilhelm then says the AI conversation has shifted quickly from raw capability to cost per task. He cites new model releases and vendor language emphasizing cheaper agentic and coding models, faster performance, and lower dollars per task. That matters because lower costs make it more plausible for AI systems to take on routine knowledge work at scale rather than remain a premium coding assistant market.The core of the article is Microsoft Office. Wilhelm notes that Microsoft turned Office from a one-time purchase into Microsoft 365, a large recurring revenue business with tens of millions of subscribers and a major productivity segment. Now, he says, late-stage unicorns and AI labs are pushing into the same territory: Anthropic's Cowork was reportedly used mostly outside software development, OpenAI merged ChatGPT and Codex into a tool for creating sheets, slides, docs, web apps, and long-running work, and other companies are building agentic coworkers that connect business data to documents, workflows, schedules, alerts, and apps.The article's caveat is that Microsoft has survived major platform shifts before. The argument is not that Office disappears quickly, but that the definition of office software is broadening from documents and spreadsheets into AI systems that can create, monitor, and act across workplace data.Read moreWhat Is Loop Engineering, and Who Owns It?Author: Nilesh Barla Published: July 11, 2026Nilesh Barla argues that “loop engineering” is becoming a distinct discipline because production AI agents now fail less at single prompts than at runtime: when to stop, what state to preserve, and how to recover after a bad step. Prompt engineering shapes one model call, and context engineering shapes what the model sees, but loop engineering shapes what a sequence of calls actually does.The killer detail is the three-primitives frame. Barla says a real agent loop needs halt conditions, state carryover, and recovery paths, then maps teams across five maturity levels. At the lowest level, an agent is just a model call in a for-loop with a step cap and raw history; by the higher levels, the system has structured state, explicit planning, replay, evaluation, and self-repair.The pull is organizational. If agents are becoming production systems rather than demos, someone has to own the runtime itself. The loop engineer is the role Barla gives to the person responsible for making long-running agent work dependable.Read more: Adaline LabsThe Fight Against AI Data Centers Is Just BeginningEmma Roth | The Verge | July 12, 2026Emma Roth argues that community resistance to data centers has moved from an early warning sign into a national political fight as AI facilities grow larger, more power-hungry, and more visible to nearby residents. The article starts with Apple's failed 2015 plan for a $1 billion data center in Athenry, Ireland, where a small group of residents challenged the project over noise, light pollution, flooding, traffic, and wildlife effects until Apple abandoned it in 2018.The current data-center buildout is presented as much larger and more contentious. Roth writes that residents now cite rising energy costs, water quality, noise, light pollution, and greenhouse gas emissions, while the U.S. Energy Information Administration expects commercial energy demand to surpass residential demand this year because of AI data centers and Goldman Sachs expects data-center power demand to double by 2027.The central evidence comes from Data Center Watch, which says protesters blocked or delayed at least 75 U.S. projects worth $130 billion from January to March, with active opposition groups more than doubling from 396 at the end of 2025 to 833 by the end of the first quarter of 2026. Roth also cites QTS abandoning a $12 billion Wisconsin campus, Delaware City regulators blocking a 580-acre project under the Coastal Zone Act, opposition stopping a QTS project in Prince William County, and pressure that pushed Kevin O'Leary to downsize the proposed 40,000-acre Project Stratos in Utah.The policy section describes a split between federal acceleration and local resistance. President Trump has treated data centers as part of the AI race with China and fast-tracked construction, while some Republican candidates are distancing themselves from that position ahead of midterms. Sanders and Ocasio-Cortez have proposed a moratorium until price and environmental protections exist, bipartisan lawmakers are backing ratepayer-protection measures, and states including Florida, Idaho, and Washington have passed rules on cost shifting, water use, and tax breaks. Roth's caveat is that the policy patchwork is still incomplete, leaving many communities to fight project by project.Read more6 months to live for open modelsAuthor: Nathan Lambert Published: July 12, 2026Nathan Lambert argues that open-weight AI models are facing their most serious policy test so far because U.S. officials are beginning to discuss concrete controls rather than abstract safety concerns. He says reported White House conversations about a new executive order may initially target Chinese-origin models and government use, but could create a broader review habit for frontier open models. His forecast is that a model above the capability range of GPT-5.5, Claude Opus 4.8, or GLM-5.2 could trigger a ban or indefinite delay within six months.The post separates two policy fights that are becoming intertwined: distillation and frontier capability. Lambert says the distillation campaign against Chinese models has become a form of regulatory capture because Anthropic and other closed-model companies would gain economically if Chinese open models were banned. He does not dismiss IP protection, but argues that if a closed model's capabilities are dangerous enough to justify restricting open models, the lab also has to explain why those capabilities are exposed through a queryable API. He cites unauthorized access to Anthropic's Mythos private beta as evidence that APIs are not automatically secure.The broader claim is that a unilateral U.S. ban would hurt positive actors more than bad actors if comparable open models remain available elsewhere. Lambert says the only durable ceiling would require global agreement, which does not exist, and that open models can improve safety by allowing broad inspection, adaptation, and understanding. His proposed near-term off-ramps are a strong U.S. open model release from companies such as Microsoft, Meta, or Reflection, and a broader coalition of open-source beneficiaries lobbying for safe rollout rather than prohibition.Read more: SourceAmericans Deserve a Dividend From AI Companies' RichesAuthor: Scott Stanford Published: July 14, 2026Scott Stanford argues that proposals to give the government a stake in AI companies miss the point unless ordinary citizens directly receive and control the upside. Sam Altman has discussed giving up equity in OpenAI, Washington already owns a stake in Intel, Nvidia is sharing China chip revenue, and Bernie Sanders wants large AI labs to contribute half their stock to a sovereign wealth fund. Stanford says those ideas all park value with the state, not with people.The killer detail is New Carlisle, Indiana, where AWS's Project Rainier is turning cornfields into one of the world's largest AI superclusters. The project is planned to run up to a million chips, draw more than two gigawatts of power, and represents an investment that has grown from $11 billion to $13.8 billion. Stanford uses that local transformation to argue that AI's public bargain should be visible at the household level.The pull is design. A citizen AI dividend would have to specify who earns a stake, how they hold it, and when they see cash. Without that mechanism, the AI wealth debate remains a fight over government balance sheets rather than public ownership.Read more: SourceWho Gets to Define the Frontier?Author: Mark Daley Published: July 14, 2026Mark Daley argues that Demis Hassabis is right to call for a serious institution to verify frontier AI systems, but that the power to test models is also the power to govern them. Hassabis's proposed Frontier AI Standards Body would get privileged pre-release access to advanced models, testing compute, held-out evaluations, support from national labs and security agencies, third-party auditors, and eventually authority to block models from the American market or coordinate a slowdown.The killer detail is Daley's constitutional objection. He says the proposal sometimes looks like a scientific lab, a standards body, an industry regulator, a licensing authority, and an emergency security council at once. Combining those roles because each requires technical expertise would be like putting the central bank, auditor-general, and Supreme Court in one building and calling it efficient.The pull is standard-setting. Daley's concern is not that verification is unnecessary, but that whoever writes the tests, decides what passes, adjudicates disputes, and grants market access may end up defining the frontier itself.Read more: SourceGPT-Red: Unlocking Self-Improvement for RobustnessOpenAI | OpenAI | July 15, 2026OpenAI describes GPT-Red as an internal automated red-teaming model trained to find prompt-injection vulnerabilities at a scale human red teams cannot match. The post says AI systems increasingly encounter third-party data through browsers, connected apps, local files, and tools, creating opportunities for malicious instructions hidden in emails, webpages, tool responses, or code repositories. Human red-teaming remains part of OpenAI's safety process, but the company says it is time-intensive and cannot generate enough diverse adversarial examples for model training.The system is trained through self-play reinforcement learning, with GPT-Red rewarded for eliciting valid failures and defender models rewarded for resisting attacks while still completing their tasks. OpenAI says the training environments specify threat models across settings such as local files, webpage banners, email bodies, and tool outputs. The model is kept separate from deployed production models because it is intentionally trained with malicious capabilities.OpenAI reports that GPT-Red generalized beyond its training set, including an internal replication of the indirect prompt-injection arena from Dziemian et al. (2025), where it found successful attacks in 84% of scenarios compared with 13% for human red-teamers. The post also says GPT-Red transferred attacks from simulation to a live autonomous vending-machine agent, causing price changes and order cancellations, and outperformed a prompted GPT-5.5 baseline against a Codex CLI agent on held-out data-exfiltration tasks.The article's main robustness claim is that OpenAI has used GPT-Red and predecessor models in training since GPT-5.3, with later GPT releases becoming more resistant to prompt injections. It says GPT-5.6 Sol has six times fewer failures on OpenAI's hardest direct prompt-injection benchmark than the best production model from four months earlier, that a “Fake Chain-of-Thought” attack class fell from more than 95% success against GPT-5.1 to below 10% against GPT-5.6 Sol, and that GPT-5.6 Sol fails on only 0.05% of GPT-Red's direct prompt injections. OpenAI says general capabilities and targeted over-refusal evaluations were not harmed, and says a preprint with more details will follow.Read moreAnthropic, Blackstone bet the next trillion-dollar AI business is implementation, not just modelsRebecca Bellan | TechCrunch | July 15, 2026Rebecca Bellan reports that Ode with Anthropic is the $1.5 billion AI implementation company launched by Anthropic with Blackstone, Hellman & Friedman, Goldman Sachs, and other backers. The article says the venture reflects a growing belief among frontier AI labs that enterprise adoption requires more than better models: customers need engineers who can embed inside businesses and turn AI into working systems.Ode was originally conceived by Blackstone after it used both large consulting firms and smaller AI services boutiques across its portfolio companies. TechCrunch reports that Fractional AI, an AI engineering services startup, stood out and was acquired by the joint venture shortly after the venture was announced. Fractional now forms the foundation of Ode, which has 100 engineers and works closely with Anthropic's applied AI team to identify where the technology can affect specific businesses.Ode CEO Chris Taylor tells TechCrunch that the company could someday become a trillion-dollar business if it scales without losing quality. He says an ideal customer is one whose CEO treats the AI project as a top one or two priority, whether it is a major product feature or the reworking of a core business process. Ode will operate under a “Claude-first” principle, using Anthropic technology whenever possible, but the article says it can use rival AI products when needed.The article's central implementation argument comes from Ode chief technologist Eddie Siegel, who says model selection matters but is not where most of the engineering effort goes. He compares it to the choice of programming language in software: one ingredient in a system that still has to be engineered. Bellan writes that Ode's challenge is hiring and training enough elite generalist engineers, many of them former founders, while competing with OpenAI's The Deployment Company and consulting giants that have built their own forward-deployed engineering teams.Read moreVint Cerf is working on a plan to unleash AI agents on the open internetTim Fernholz | TechCrunch | July 15, 2026Tim Fernholz reports that Vint Cerf, after leaving Google, is advising Innovation Labs on an open architecture for identifying AI agents online. Innovation Labs is a subsidiary of Identity Digital, a DNS registry company, and its proposal is to use domain-name infrastructure as part of a system for agent identity, accountability, and auditability. The premise is that agents will need a way to identify themselves if they move beyond proprietary systems and begin interacting across the open internet.The concrete proposal is DNSid, a registry that links an AI agent to an existing internet domain and uses cryptographic proofs to log its registration over time. Innovation Labs says it is trialing the standard with unnamed hyperscalers and identity companies. Cerf frames the problem around authority and accountability: what authority an agent has, where that authority came from, who is accountable for the agent's behavior, how its identity is established, and why anyone should trust it.The article's caveat is that standards are still emerging and agents are more active than static domains. Cerf says the period may be both fascinating and exasperating because the functionality is powerful and interoperability is unresolved. He compares the adoption problem to TCP/IP: competing systems may not work together until users push for functional interoperation. He also says an agentic economy is not inevitable, but that people will try to build it because delegating work to agents will be easier.Read more: TechCrunchxai-org/grok-build, now open sourceAuthor: Simon Willison Published: July 15, 2026Simon Willison argues that xAI's decision to open-source Grok Build is best understood as a trust repair move after a severe privacy failure. The CLI had triggered backlash when users realized that running it in a directory could upload the entire directory to xAI's Google Cloud buckets, including one user's reported SSH keys, password manager database, documents, photos, and videos. xAI disabled the feature, said previously retained coding data would be deleted, and released the code under Apache 2.0.The killer detail is what the codebase reveals. Willison counts 844,530 lines of Rust, only about 3% of which appears vendored, and finds remnants of the upload system still present but disabled: gcs.rs contains Google Cloud upload code, while upload_session_state() now returns a hard-coded session_state_upload_unavailable error. He also notes copied or ported tool implementations from Codex and OpenCode, prompt files, and a terminal Mermaid renderer.The pull is that terminal coding agents are becoming large, intricate software systems in their own right. The privacy failure mattered because these tools operate inside the directories where developers keep their most sensitive work; the open-source release matters because trust now depends on inspecting what an agent can see, send, and do.Read more: SourceThe Pulse: What can we learn from Bun's rapid Rust rewrite with AI?Author: Gergely Orosz and Ivan Klaric Published: July 16, 2026Gergely Orosz and Ivan Klaric argue that Bun's AI-assisted rewrite from Zig to Rust is a practical sign of how software engineering changes when models can take on large, bounded migrations with clear feedback loops. The piece does not treat the rewrite as magic: Jarred Sumner first spent hours turning design judgment into a detailed porting guide, then used adversarial review, parallel agents, compiler errors, and tests to force the work toward correctness.The killer detail is the scale. Bun had 535,496 lines of Zig, 1,448 files, and 22 million monthly downloads, making a conventional rewrite a year-long freeze the team could not justify. Using Fable, Sumner split the work across 64 agents, produced about 6,500 commits, and got the migration done in 11 days at an estimated API cost of $165,000.The pull is economic, not theatrical. If a one- or two-year migration can become an 11-day project, AI coding is not just faster autocomplete; it changes which technical debts are worth paying down.Read more: SourceOrphan risks at the frontier of artificial intelligenceAuthor: Andrew Maynard Published: July 16, 2026Andrew Maynard argues that frontier AI safety frameworks are creating “orphan risks”: harms that companies can see, but do not formally own because they are hard to quantify, do not fit catastrophic-risk thresholds, or fall outside audit-friendly compliance machinery. His target is not existing frontier safety work, but the narrowing effect that happens when private companies decide which risks count as governable.The killer detail is Maynard's contrast between measurable model dangers and threats to value. He points to Meta's three-day Galactica collapse, OpenAI's 2023 board crisis, safety-team departures, and wellbeing litigation as examples of risks that damaged trust, culture, legitimacy, or users without fitting cleanly into conventional model-risk categories. The proposed fix is an orphan-risk register: a public record of risks a company considered and chose not to manage, with reasons.The pull is accountability. Frontier developers' internal scoping choices have become a de facto layer of public governance, so the question is no longer only which risks they manage, but which risks they quietly leave outside the frame.Read more: SourceThe Lab of the Future Should Feel Like a Data CenterLatent.Space with Andy Beam and Rafa Gomez-Bombarelli | Latent.Space | July 16, 2026Latent.Space interviews Lila Sciences CTO Andy Beam and chief science officer for physical sciences Rafa Gomez-Bombarelli about the company's attempt to build an AI-run science factory. The post describes Lila's thesis as treating the lab itself as an “infinite token generator”: if internet data drove the first era of AI scaling, experimentally verified scientific data may be the next scarce training source. Lila is trying to produce that data with robotics, lab instruments, orchestration software, and AI models wired into the wet lab.The central analogy is the lab as data center. Instruments are nodes on a graph, a magnetically levitating transport layer moves materials between them, and experiment scheduling looks like a compute queue. Beam says Lila is not simply an automation company, because the point is not just throughput; it is flexibility, generalization, and experiment capture. The post says Lila has built more than 10 trillion experimentally validated “scientific reasoning tokens,” not internet text or biological sequences.The interview ranges across biology, chemistry, drug discovery, materials science, and the limits of automation. It notes that Lila rebuilt one gas-sorption measurement to run roughly 2,500 times faster, claims its general models can transfer priors from small-molecule chemistry to metal-organic frameworks for carbon capture, and describes model-suggested platinum-group-free electrocatalysts that moved from looking boring or wrong to becoming strong performers. The caveats are physical: experiments have runtimes, biology cannot always be accelerated, chains of thought can be unreliable narrators, and reward hacking becomes more dangerous when a model controls a real lab.Read more: Latent.SpaceWhy AMI Labs' Alexandre LeBrun won't call his AI “AGI” or “superintelligence”Kate Park | TechCrunch | July 16, 2026Kate Park interviews AMI Labs CEO Alexandre LeBrun about why Yann LeCun's world-model startup avoids the language of “AGI” and “superintelligence.” LeBrun says the terms are not useful because they lack stable definitions: “We never used the word AGI. And I just noticed that nobody is using it anymore; they switched to superintelligence.” His argument is that the practical frontier is not a label, but whether AI systems can understand and predict real-world states.The article explains the world-model thesis by contrasting language prediction with physical-state prediction. A large language model predicts the next word; a world model predicts the next state, such as what happens when a glass tips over. LeBrun says LLMs remain complementary and efficient for language, but the physical world is where current AI is weak. Robotics is the clearest case: hardware has advanced quickly, but robots are still brittle outside controlled routines because they lack context and situational understanding.AMI is still pre-product, but TechCrunch reports that LeBrun was in Seoul looking for industrial partners, researchers, and global companies. He says world models cannot be built entirely inside a lab because they need access to real environments. That is why South Korea appeals to AMI: robotics, semiconductors, manufacturing, and fast adoption create the kind of hardware-heavy context that software-only AI has barely touched.Read more: TechCrunchKimi K3 Tech Blog: Open Frontier IntelligenceKimi | Kimi | July 16, 2026Kimi introduces Kimi K3 as an open 3T-class frontier model aimed at coding, knowledge work, reasoning, multimodality, and long-context agentic use. The source describes the model as a 2.8T-parameter system built on Kimi Delta Attention and Attention Residuals, with native multimodality and a 1M-token context window. It says Moonshot AI plans to release model weights by July 27.The post presents K3 through benchmark and use-case sections rather than as a general product announcement. It reports results across coding, productivity, agentic, and multimodal evaluations, including DeepSWE, Terminal-Bench 2.1, Program Bench, SWE Marathon, FrontierSWE, PostTrain Bench, OfficeQA Pro, SpreadsheetBench 2, MCP Atlas, AutomationBench, BrowseComp, GDPval-AA v2, AA-Briefcase, MMMU-Pro, MathVision, BabyVision, OmniDocBench, and PerceptionBench. The source says all reported K3 results use maximum reasoning effort with temperature and top-p set to 1.0, and that different benchmark comparisons use KimiCode, Claude Code, or Codex harnesses depending on the test.Kimi's caveats are unusually concrete. The limitations section says K3 was trained in preserved thinking-history mode, so quality may become unstable if an agent harness does not pass historical thinking content correctly or if an ongoing session switches to K3 midstream. It also says K3's emphasis on long-horizon tasks can make it excessively proactive when it encounters minor issues or ambiguous intent, and recommends imposing explicit behavioral constraints for applications that require strict boundaries. The post adds that K3 remains behind Claude Fable 5 and GPT 5.6 Sol in user experience despite being competitive overall.Read moreVenture CapitalThree Years InAuthor: Tomasz Tunguz Published: July 10, 2026Tomasz Tunguz marks Theory Ventures' third anniversary by arguing that AI's central market effect is time compression. In his telling, model release cycles, company revenue milestones, enterprise adoption, and venture categories have all accelerated. Seed, Series A, and Series B still exist as financing labels, but they no longer cleanly describe company maturity when some seed rounds are larger than IPOs and the best AI companies can mature much earlier than prior software companies.The killer detail is the shift from models to inference. Tunguz argues that inference has become the dominant AI market because workloads and buyer preferences are fragmenting: video, batch, local, agentic, and real-time tasks each create different infrastructure needs. He compares this to databases splitting into OLTP, OLAP, vector, and streaming categories, with AI pushing the same specialization into inference infrastructure.The pull is that Theory sees the AI-native venture firm as part of the same pattern. The firm says it has analyzed twice as many investment opportunities with three investors working alongside a nine-person intelligence organization, using agents and research systems to map markets, source companies, and support diligence. The piece is both a market map and a statement about how venture itself is being rebuilt by the technology it funds.Read more: LinkedInVenture Has Rarely Looked More BifurcatedAuthor: Beezer Clarkson Published: July 14, 2026Beezer Clarkson points to PitchBook's Q2 report as evidence that the U.S. venture market has split into two very different realities. AI now accounts for more than 60 percent of all U.S. venture deal value, meaning the headline market can look active and well-funded even while much of the non-AI market is dealing with a much colder liquidity and fundraising environment.The thread uses that split as the setup for Clarkson's latest Origins episode with Alec Litowitz, founder of Magnetar and QStar Capital and one of Citadel's original founding partners. Clarkson says markets like this are periods of genuine uncertainty, not merely ordinary risk, which is why Litowitz's Adaptability Quotient framework is relevant.The embedded clip makes the liquidity point concrete. Litowitz says DPI is “the resolution of uncertainty” because it converts an uncertain investment into actual cash returned to LPs. In his framing, a realized dollar is a real mark, while TVPI remains uncertain until it is realized.The killer detail is the distinction between pricing risk and resolving uncertainty. Litowitz's perspective matters because QStar is a SpaceX investor and Clarkson says the conversation happened just before one of venture's most consequential IPOs. The episode's stated questions are why venture remains a way to gain exposure to innovation, how AI is changing what is investable, why liquidity is ultimately a function of time, and why uncertainty requires a different decision framework from risk.Read more: XThe Best Angel Investors in the US: Who Backs the Most Unicorns, and Who's Active NowAuthor: Ilya Strebulaev Published: July 10, 2026Ilya Strebulaev ranks angels, angel groups, accelerators, and incubators by lifetime U.S. unicorn investments, counting checks written before a company reached unicorn status. The top of the combined list is dominated by organizations: Y Combinator leads with 113 unicorn investments, followed by Plug and Play at 52 and 500 Global at 41. Sand Hill Angels is the highest-ranked angel group at 31.The killer detail is how quickly the list changes below the biggest accelerators. Strebulaev says 271 of the 304 investors in the Top 200 are individuals, or 89%. In the top 100, individuals are 91%. That makes the market underneath the large accelerator counts look much more personal: mostly operators and individual angels writing early checks from their own networks.The pull is the ranking's own caveat. Strebulaev writes that every lifetime leaderboard has a blind spot because many of the unicorns behind those totals were founded a decade or more ago, and some angels have since moved into formal funds, slowed down, or stopped investing. His post therefore separates lifetime performance from recent cohorts, including companies founded in 2015 or later and 2020 or later. For founders or allocators making current decisions, that distinction matters: a career record and a current record are not the same measure.Read more: Ilya StrebulaevAre Prediction Markets Doomed to Fail?Author: Contrary Published: July 16, 2026Contrary argues that prediction markets' current boom depends on whether platforms can prove they are more than regulated gambling with exchange-style branding. Kalshi and Polymarket have reached mass cultural, investor, and regulatory attention, but the article says the underlying idea is old: academic markets, corporate forecasting tools, Intrade, PredictIt, and other predecessors all struggled with the same linked problems of liquidity, legality, and user appeal.The killer detail is the comparison with sportsbooks. Prediction markets present themselves as peer-to-peer, transparent, and non-house-based, but sports contracts reportedly account for more than 90 percent of Kalshi trading, and the article says the platforms keep a much thinner slice of volume than sportsbooks. A market can therefore show sports-betting-scale handle while generating far less revenue.The pull is that the product's hardest problem may be distribution of wins. If a small group of sharp traders captures most profits while casual users lose interest, prediction markets may become valuable data feeds and professional tools before they become durable consumer networks.Read more: SourceRegulationExclusive: The Next Frontier of the Deportation Wars: College CampusesAuthor: Adrian Carrasquillo Published: July 11, 2026Adrian Carrasquillo reports that college campuses are becoming a new front in the fight over immigration enforcement because automatic license plate readers can turn ordinary campus security infrastructure into searchable location data. His thesis is that Flock Safety's camera network, even without direct ICE or DHS contracts, can feed deportation enforcement through local police partnerships and data-sharing practices.The killer detail is the campaign target. The Emergency Campaign to Support Higher Education, working with Schools Drop ICE, is focusing on 75 colleges and universities publicly identified as having Flock contracts. Flock says it has no ICE or DHS contracts, but activists argue the risk comes through local agencies that coordinate with federal authorities and run searches on their behalf.The pull is broader than immigration. Carrasquillo notes that license plate readers have already been abused by officers for stalking, and that Flock's AI search features can identify more than plates, including bumper stickers. A campus safety tool can become a political surveillance system when the data layer is searchable.Read more: The BulwarkThe Supreme Court Broke Independent Agencies. Here's a Way to Slow the Damage.Author: Todd Phillips Published: July 12, 2026Todd Phillips argues that the Supreme Court's decision in Trump v. Slaughter damaged independent agencies by ending for-cause removal protections, but did not leave Congress powerless. The ruling weakens the old model in which commissioners at bodies such as the FTC, NLRB, CPSC, SEC, and CFTC could be insulated from dismissal over policy disagreements. Phillips says the next fight is whether presidents can turn nominally bipartisan commissions into one-party instruments.The killer detail is the procedural fix: quorum rules. Phillips proposes that Congress require bipartisan slates of commissioners to be seated before independent agencies can act. A president

Why are some countries richer than others, even though money, people and ideas can flow freely round the world? Why is it so hard for a country to turn things around and become rich? Are illiberal leaders like Trump good for their economy? What role do sovereign wealth funds play? Nobel prize winning economist Simon Johnson gives us his theory on the damage extractive institutions do to wealth disparity. As a leading professor at MIT and former chief economist at the IMF, Robert and Steph quiz him on how the history of colonisation has shaped world economics and what can be done about it. The Rest is Money is brought to you by Octopus Energy, Britain's smart energy pioneer. Email: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠the⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠restismoney@goalhanger.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@TheRestIsMoney⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Instagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@TheRestIsMoney⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@RestIsMoney⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Advertise with us: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Partnerships@goalhanger.com⁠ For more Goalhanger Podcasts, head to ⁠www.goalhanger.com⁠ Video Editor: Dylan Bonham Producer: Isabelle Bougeard Exec Producers: Chris Sawyer and Tom Whiter Learn more about your ad choices. Visit podcastchoices.com/adchoices

Who kept the courts sitting and the streetlights lit when the state had almost no money to pay anyone?Two hundred years ago, British local government ran on unpaid labour. In a parliamentary survey of the boroughs from 1835, two in three of the people doing local government work were not paid at all.James Robinson (University of Chicago, CEPR) explains how this succeeded in this week's episode of VoxTalks Economics. Robinson and his co-authors call this the "embedded state". Members of the elite willingly took the unpaid jobs because the postings carried prestige and led to Parliament, promotion or a paid post. Less glamorous or dead-end postings -- the jailer for example -- had to be paidBut the unpaid officers were more productive than the paid ones.Robinson argues this is not a quirk of England at that time. Rwanda runs a high-capacity state today on much the same basis, without ever raising the taxes the IMF says a proper government needs. The lesson for anyone trying to make government work: start with the society, not the tax code.New episode of VoxTalks Economics. Link in bio.Image: William Benjamin Watkins by George Patten / Manchester Town Hall.The research behind this episode:Heldring, Leander, Davis Kedrosky, James A. Robinson, and Matthias Weigand. 2026. "The Success of the Embedded State in England." CEPR Discussion Paper No. 21460. Centre for Economic Policy Research, London. To cite this episode:Phillips, Tim, and James A. Robinson. 2026. "The success of the embedded state." VoxTalks Economics (podcast). Assign this as extra listening. The citation above is formatted and ready for a reading list or VLE.About the guestJames A. Robinson is University Professor at the Harris School of Public Policy and the Department of Political Science, University of Chicago, and a Research Fellow at the Centre for Economic Policy Research. His research spans comparative political and economic development, state capacity, and the long-run relationship between institutions and prosperity, with fieldwork across sub-Saharan Africa and Latin America. He shared the 2024 Nobel Memorial Prize in Economic Sciences with Daron Acemoglu and Simon Johnson.Research cited in this episodeThe 1835 parliamentary report. After the 1832 Reform Act, Parliament sent lawyers to roughly three hundred of the largest boroughs to record who worked for each borough government, what they did, whether they were paid, how much, and how well the job was done. The commissioners graded public goods directly; whether a jail existed, and if so whether its condition was satisfactory. The 3,500-page report is the factual basis for the paper, and it survives because Parliament itself did not know how these idiosyncratic, often medieval borough governments worked.The fiscal-military state. The dominant account of British state formation comes from John Brewer's The Sinews of Power (1989), which traces the rise of a tax-raising, salaried fiscal state after the Glorious Revolution of 1688. Robinson's point is that this describes 20,000 officials in London; across the rest of the country, where fiscal resources were thin, most government work was done for free.Mark Goldie and the unpaid office-holder. The historian and political theorist Mark Goldie documented the scale of unpaid local office-holding in earlier work; Robinson and his co-authors took that observation and asked how to study it systematically, which led them to the 1835 report.The embedded state. A state has high capacity when it can implement policy and provide public goods. The embedded state does this without the fiscal resources to fund a modern bureaucracy, by drawing on the social structure of the society it governs to motivate people to do government work unpaid. Because that social structure differs from place to place, embedding looks different in 1830s Britain, in modern Rwanda, and in 1970s South Korea; understanding the state means understanding the sociology beneath it.Rwanda's state capacity. Robinson and Leander Heldring also study the organisation of the state in Rwanda, where most government workers are unpaid and the country has never raised the 15% of national income in taxes that the International Monetary Fund treats as the threshold for a functioning state, yet implements policy effectively.Elinor Ostrom and the commons. Elinor Ostrom won the 2009 Nobel Memorial Prize for showing that communities can organise to provide and govern shared resources without the state. Robinson's argument is that the interface between such collective provision and the state is productive rather than antagonistic.Somaliland and the Guurti. Somaliland has an elaborate clan structure, and its upper house, the Guurti, represents the clans. Robinson offers it as a case where anyone trying to improve public good provision should start from the existing social structure rather than from tax reform.The History of British Local Government. Beatrice and Sidney Webb's nine-volume history of English local government documents the medieval charters, inherited land and bequests that determined how much fiscal capacity each borough had. That historically determined variation in whether a borough could afford to pay its officers is what the paper uses to identify the effect of pay on performance.More VoxTalks Economics episodesNobel Special - James Robinson on antisocial norms. The saying “don't be a toad” in Colombia tells people to mind their own business and not to tell on others. The warning that “snitches get stitches” is common to many societies. It's easy to imagine why groups adopt prosocial norms like sharing and volunteering. But what sustains an “antisocial” norm?

Simon Johnson & Elisabeth Reynolds, professors at MIT, join Bloomberg's Tom Keene and Paul Sweeney to discuss how six sectors may determine the future of America's tech leadership.See omnystudio.com/listener for privacy information.

As the use of AI in finance becomes more pervasive -- in trading algorithms and credit underwriting, to insurance claims processing -- what benefits and risks do these systems pose? Gary Gensler joins EconoFact Chats to discuss how AI is lowering costs and broadening access to financial services, but also creating new challenges around explainability, bias, and accuracy. Gary is Professor of the Practice of Global Economics and Management as well as of Finance at the MIT Sloan School of Management. He served as Chair of the Securities and Exchange Commission. Along with Simon Johnson, he hosts the podcast Power and Consequences.

In this bonus episode, Nobel Prize-winning economist Daron Acemoglu joins Sam to challenge some of the most common assumptions about artificial intelligence's future. Drawing on his book Power and Progress, Daron argues that technology doesn't have a fixed destiny — and that today's choices will determine whether AI boosts workers or simply accelerates automation and inequality. He makes a case for focusing on new tasks that complement human skills, rather than replacing them, and warns that current incentives push AI toward centralization and automation by default. The conversation tackles productivity myths, reliability risks, and why regulation should proactively steer AI toward social good. Read the episode transcript here. Guest bio: Daron Acemoglu is an institute professor at MIT, faculty codirector of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work, and a research affiliate at MIT's newly established Blueprint Labs. He is an elected fellow of the National Academy of Sciences, American Philosophical Society, the British Academy of Sciences, the Turkish Academy of Sciences, the American Academy of Arts and Sciences, the Econometric Society, the European Economic Association, and the Society of Labor Economists. He is also a member of the Group of Thirty. He has authored six books, including Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity with Simon Johnson. His work in economics has been recognized around the world, notably with the Nobel Prize in economic sciences, along with co-laureates Johnson and James A. Robinson, in 2024. *Please take our listener survey: ⁠⁠mitsmr.com/podcastsurvey⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

【百花新闻信 Baihua Newsletter】 百花 Baihua Newsletter 正式上线了。也希望疲惫娇娃的听众们去订阅这个新闻信。 如果你一直在听《疲惫娇娃》《美轮美换》，或者来过我们的读书会、线下活动，你其实已经在百花的世界里了。只是现在，我们想把这个世界更系统、更持续地建起来。我们想记录中文播客圈正在发生什么，记录中国互联网的公共讨论空间，也记录这一代数字原住民华语创作者如何在"平行互联网"之间生存、创造、发声，这个新闻信是双语的，我们几个女的和其他百花成员会轮流写作。 请点击这里订阅：https://baihua.substack.com/ 如果打不开这个链接，请用以下问卷留下你的邮箱账号：https://wj.qq.com/s2/25773709/59ax/ Baihua Newsletter has officially launched. We warmly invite listeners of CyberPink to subscribe. If you've been listening to CyberPink or Mei Lun Mei Huan, or have joined our book clubs and offline events, you've already been part of the Baihua world. Now, we want to build that world in a more systematic and sustainable way. Through Baihua, we aim to document what's happening in the Chinese-language podcast sphere, trace the evolving public discourse on the Chinese internet, and explore how a generation of digital-native Chinese creators are surviving, creating, and speaking across what we call “parallel internets.” The newsletter is bilingual. We — along with other Baihua contributors — will take turns writing. Subscribe here: https://baihua.substack.com/ If you can't open the URL above, leave your email address here: https://wj.qq.com/s2/25773709/59ax/ 【聊了什么The What】 这期节目是vibe shift三部曲的最后一集——在酝酿了很久以后，我们终于找到了一个适合开启的角度——“匮乏”。这里的匮乏不仅仅指经济指标上的衰退（如好莱坞罢工、票房崩溃、生活成本危机），更指向一种集体心理状态：对美好未来的想象力丧失了。 当“信心”消失，欲望就变成了苦涩的愤怒和嘲讽。我们聊到了韩国电影中为了生存系统性谋杀竞争对手的失业男主，聊到了好莱坞自由主义叙事的全面崩塌，以及 Gen Z 为何不再相信《哈利·波特》式的英雄主义。在这样一个极化、原子化、被算法裹挟的时代，我们该如何寻找解药？答案或许在于做一些“低效”但具体的事情，比如给邻居送菜，比如慢慢地讲一个故事。 This episode is the final installment of our “Vibe Shift” trilogy. After circling the theme for a long time, we finally found the right entry point: scarcity. Scarcity here doesn't only refer to economic downturns — Hollywood strikes, collapsing box office numbers, or the cost-of-living crisis. It points to something deeper: a collective psychological state in which the imagination of a better future has eroded. When confidence disappears, desire curdles into resentment, sarcasm, and anger. We talk about a Korean film in which an unemployed man systemically eliminates his competitors just to survive. We discuss the collapse of Hollywood's liberal narrative framework. We explore why Gen Z no longer believes in Harry Potter–style heroism. In an era defined by polarization, atomization, and algorithmic manipulation, how do we find an antidote? Perhaps the answer lies in doing things that feel inefficient but concrete — bringing vegetables to a neighbor, telling a story slowly and carefully. 【时间轴 The When】 00:00 什么是“匮乏感”？它不只是缺钱，而是对未来失去信心。当希望消失，欲望会转化为愤怒和犬儒。 05:30 从《无路可逃》和《爱丁顿》说起。当资源紧缩，他人变成路障。传统“供养者”男性叙事在现代系统中崩塌。 12:11 自由主义叙事开始失效。观众厌倦好莱坞的说教，《The Studio》揭示的是文化工业的瘫痪与精英脱节。 23:36 代际断裂。为什么 Gen Z 对《哈利波特》那种九十年代式的乐观主义越来越无感，Gen Z 成长于极化与停滞之中，不再相信善恶分明的世界。 36:00 我们开始怀旧：布拉德·皮特和《F1》是一个典型例子，电影构建了一个没有政治争议、只有输赢规则的世界。传统男性气概重新被召唤。你爹还是你爹。这种叙事满足了人们对确定性的渴望，也提供了一种逃避复杂现实的方式。 47:50 性别角色回潮。《爱情盲选》和 tradwife 现象反映了在极化时代中对安全感的表演式追寻。 55: 50 AI 并未带来连接，反而放大分裂，我们开始怀疑“科技救世”的神话。《神奇四侠》中的技术乐观主义不复存在。 1:23:30 西方社会 生活成本危机加剧匮乏感。算法利用焦虑制造争吵，社交网络赛博巴尔干化是什么？ 1:35:30 结语 拒绝犬儒，从具体行动开始。真实的连接或许是对抗虚无的唯一方式。 00:00 What is “scarcity”? It's not just financial lack, but a loss of faith in the future. When hope disappears, desire turns into anger and cynicism. 05:30 We begin with No Other Choice and Eddington. As resources shrink, other people become obstacles. The traditional male “provider” narrative collapses within the modern system. 12:11 The liberal narrative loses its grip. Audiences are exhausted by Hollywood moralizing. The Studio exposes paralysis within the cultural industry and its detachment from ordinary life. 23:36 A generational rupture. Why Gen Z no longer connects with 1990s optimism like Harry Potter. Raised amid polarization and stagnation, they no longer believe in a morally clear world. 36:00 We turn to nostalgia. Brad Pitt and F1 serve as a key example. The film constructs a world without political conflict — only winners and losers. Traditional masculinity is revived. “Daddy is still daddy.” It satisfies a longing for certainty and offers escape from complexity. 47:50 The return of gender roles. Love Is Blind and the tradwife phenomenon reflect a performative search for safety in a polarized age. 55:50 AI did not bring connection; it amplified division. We begin to question the myth of technological salvation. The technological optimism of Fantastic Four no longer holds. 1:23:30 The Western cost-of-living crisis deepens scarcity. Algorithms exploit anxiety and manufacture endless conflict. What does cyber-Balkanization of social networks mean? 1:35:30 Conclusion. Reject cynicism and begin with concrete action. Real human connection may be the only antidote to nihilism. 【拓展链接 The Links】 阿花： Beyond the Machine: Creative agency in the AI landscape Personal canon by Celine Nguyen Remaking Liberalism: The Past, Present, and Future of Freedom by Daron Acemoglu and Simon Johnson 配图：从1998年开始的价格变化 影视/剧集： 电影《无路可逃》(No Other Choice / The AX) 电影《爱丁顿》(Eddington) 电影《F1》 电影《神奇四侠》(Fantastic 4) 剧集《The Studio》 真人秀《爱情盲选》(Love is Blind) 剧集《Abbott Elementary》 书籍/人物/概念： Daron Acemoglu (经济学家) Hanif Abdurraqib (作家/诗人) Tradwife (传统家庭主妇风潮) Cyber-Balkanization (赛博巴尔干化) Identity Politics (身份政治) 【疲惫红书 CyberRed】 除了播客以外，疲惫娇娃的几个女的在小红书上开了官方账号，我们会不定期发布【疲惫在读】、【疲惫在看】、【疲惫旅行】、【疲惫Vlog】等等更加轻盈、好玩、实验性质的内容。如果你想知道除了播客以外我们在关注什么，快来小红书评论区和我们互动。 Apart from the podcast, we have set up an official account on Xiaohongshu. We will periodically post content such as “CyberPink Reading,” “CyberPink Watching,” “CyberPink Traveling,” “CyberPink Vlog,” and more. Those are lighter, more fun and more experimental stuff about our lives. Leave us some comments on Xiaohongshu! 【买咖啡 Please Support Us】 如果喜欢这期节目并愿意想要给我们买杯咖啡： 海外用户：https://www.patreon.com/cyberpinkfm 海内用户：https://afdian.com/a/cyberpinkfm 商务合作邮箱：cyberpinkfm@gmail.com 商务合作微信：CyberPink2022 If you like our show and want to support us, please consider the following: Those Abroad: https://www.patreon.com/cyberpinkfm Those in China: https://afdian.com/a/cyberpinkfm Business Inquiries Email: cyberpinkfm@gmail.com Business Inquiries WeChat: CyberPink2022

Economic policy in the second Trump administration continues to undergo significant change. Many of these changes have been enacted through executive orders. What effect have these policies had on economic growth, scientific research, and on American institutions thus far? How might they impact U.S. leadership over the long-term? Simon Johnson joins EconoFact Chats to discuss these questions, drawing on a new book he co-edited, 'The Economic Consequences of the Second Trump Administration: A Preliminary Assessment.' Simon is the Ronald A. Kurtz Professor of Entrepreneurship at the MIT Sloan School of Management, where he heads the Global Economics and Management Group. He served as Chief Economist at the International Monetary Fund in 2007–2008 and was a co-recipient of the Nobel Prize in Economics in 2024.

AI is reshaping national power and governance. Drawing on India's digital public infrastructure, Jayant Sinha and Vasant Dhar discuss innovation and sovereignty over compute, data consent and privacy by design in Episode 103 of Brave New World. Useful Resources: 1. Jayant Sinha2. Eversource Capital3. India's Green Startups: Jayant Sinha and Sandeep Bhammer4. Nandan Nilekani5. Brave New World Episode 15: Nandan Nilekani on an Egalitarian Internet6. Brave New World Episode 50: Pramod Varma on India's Digital Empowerment 7. iSpirit8. Unique Identification Authority Of India9. Unified Payments Interface10. M-Pesa11. DigiYatra. 12. Australia has banned social media for kids under 16. 13. Data Empowerment and Protection Architecture, DEPA14. Paul Gruenwald, Global Chief Economist, S&P Global15. Daron Acemoglu, Simon Johnson, James A. Robinson. 16. Neeraj Chopra17. Thinking with Machines, The Brave New World of AI: Vasant Dhar18. Battery Smart19. Nutrifresh20. Zero Cow21. RevFin22. Upside Foods23. Brave New World Episode 93: Uma Valeti on Cultivating Meat24. Brave New World Episode 101: Deepak Chopra On Consciousness and Reality25. Geoffrey Hinton26. Asimov's Laws27. Jonathan Haidt28. The Anxious Generation: Jonathan Haidt Check out Vasant Dhar's newsletter on Substack. The subscription is free! Order Vasant Dhar's new book, Thinking With Machines

What if AI is repeating the same mistakes society made during the Industrial Revolution? In this episode of Technovation, Peter is joined by Nobel Prize Laureate in Economics and Ronald A. Kurtz Professor of Entrepreneurship at the MIT Sloan School of Management Simon Johnson. Throughout their conversation, they explore why automation has historically failed to deliver shared prosperity and why artificial intelligence may be following the same path. Drawing on centuries of economic history, Johnson explains how mechanization once displaced workers faster than new jobs were created, fueling inequality and social unrest. Together, they discuss what today's AI leaders must learn from history, why institutions matter more than technology alone, and how workforce anxiety is an early warning sign of deeper structural problems. Key topics include: Automation vs. job creation AI's impact on entry-level and knowledge work Workforce polarization and regional inequality Lessons from the Industrial Revolution for today's leaders What it takes to align innovation with shared prosperity

داستان الهام بخش برای ملت‌هایی که دنبال توسعه می‌گردن، وقتی ایران داشت گذشته رو خرج می‌کرد ولی کره آینده رو می‌ساخت.متن: بهجت بندری، علی بندری با راهنمایی آرش رئیسی‌نژاد | ویدیو و صدا: حمیدرضا فرخ‌سرشتبرای دیدن ویدیوی این اپیزود اگر ایران هستید وی‌پی‌ان بزنید و روی لینک زیر کلیک کنیدیوتیوب بی‌پلاسکانال تلگرام بی‌پلاسمنابع و لینک‌هایی برای کنجکاوی بیشترSouth Korean Development Model by Milan LajčiakThe chaebol and the US military–industrial complex: Cold War geopolitical economy and South Korean industrialization by Jim GlassmanThe democratic transition by Fabrice Murtin and Romain WacziargPopulation Change and Development in KoreaINSTITUTIONS AS THE FUNDAMENTAL CAUSE OF LONG-RUN GROWTH by Daron Acemoglu, Simon Johnson, James RobinsonThe Park Chung Hee Era by by UNG-KOOK KIMKorea's Development Under Park Chung Hee By Hyung-A KimKorea's Rapid Export Expansion in the 1960s: How It Began,JUNGHO YOO*THE KOREAN MIRACLE (1962-1980) REVISITED: MYTHS AND REALITIES IN STRATEGY AND DEVELOPMENT Kwan S. KimLand Reform in Korea, 1950, Shin, Yong-HaThe Economic and Social Modernization of the Republic of Korea: 1945-1975,EDWARD S. MASONTenancy, Land Redistribution, and Economic Growth A Case of Korea, 1920-1960, Jea Hwan Hong, Duol Kimچرا ملت‌ها شکست می‌خورند، دارون عجم اوغلو، جیمز رابینسونراه باریک آزادی، دارون عجم اوغلو، جیمز رابینسونکره بعد از جنگ: اصلاحات ارضی (شروع ازسینگمان ری (Syngman Rhee) اوج در دوره پارک) Hosted on Acast. See acast.com/privacy for more information.

C dans l'air du 4 septembre 2025 - Faut-il plus taxer les riches ?En cette rentrée, la question revient en force dans le débat politique. Et cette fois, c'est le Parti socialiste qui remet le sujet sur la table en proposant d'inclure la taxe Zucman au budget 2026, sur lequel le gouvernement promet de faire des compromis, alors qu'il se trouve sur la sellette à l'approche d'un vote de confiance prévu le 8 septembre.Mais de quoi parle-t-on ? Qu'est-ce que la taxe Zucman, au cœur du contre-budget du PS ? Adoptée à l'Assemblée nationale en février dernier (par 116 voix contre 39), puis rejetée au Sénat en juin, cette mesure, inspirée des travaux de l'économiste Gabriel Zucman (qui lui a donné son nom), propose un impôt plancher sur la fortune (IPF) équivalent à 2 % du patrimoine net des ultra-riches dépassant 100 millions d'euros — soit 0,01 % des contribuables, environ 1 800 foyers français. Avec à la clé : entre 15 et 25 milliards de recettes supplémentaires.Soutenue par la gauche, contestée par la droite et l'extrême droite, la mise en œuvre de cette taxe soulève de nombreux débats depuis des semaines.Cet été, sept prix Nobel d'économie ont apporté leur soutien à la mesure : Daron Acemoglu (2024), George Akerlof (2001), Abhijit Banerjee (2019), Esther Duflo (2019), Simon Johnson (2024), Paul Krugman (2008) et Joseph Stiglitz (2001), réunis dans une tribune du Monde parue en juillet. D'autres, en revanche, comme le président du Medef, Patrick Martin, évoquent la menace de l'exil fiscal.Parallèlement, alors qu'une vague historique de transmissions se profile, les propositions de réforme de l'impôt sur les successions se multiplient. Dans un entretien accordé aux Échos, la présidente de l'Assemblée nationale, Yaël Braun-Pivet (Renaissance), évoque la nécessité de ne pas « exclure d'emblée toute hausse d'impôts » et de « se pencher sur la taxation des "super-héritages" ». L'élue des Yvelines explique : « 0,1 % des héritiers reçoivent des montants supérieurs à 13 millions d'euros et ne paient en moyenne que 10 % de droits de succession. »Aujourd'hui, près de la moitié des ménages français ne touche pas d'héritage. Parmi ceux qui en bénéficient, 87 % ne paient aucun droit de succession (chaque parent peut donner jusqu'à 100 000 euros par enfant sans qu'il y ait de droits de donation à payer). Au-dessus, le taux moyen d'imposition effectif sur les successions en France est d'environ 5 %.Autre sujet dans le débat : le train de vie des élus. En réponse à de nombreux messages de Français, le Premier ministre a promis de passer au crible et de supprimer d'éventuels avantages indus dont bénéficieraient les responsables politiques. Il a confié une mission à l'ex-député socialiste René Dosière pour les identifier.LES EXPERTS :- EMMANUEL DUTEIL - Directeur de la rédaction - L'Usine Nouvelle - THOMAS PORCHER - Économiste, professeur à la Paris School of Business, auteur de Le vacataire - RAPHAËLLE BACQUÉ - Grand reporter - Le Monde , auteure de Successions - CAROLINE MICHEL-AGUIRRE - Grand reporter au service France – Nouvel Obs

Simon Johnson, Nobel-winning economist, joined Marketplace's Meghan McCarty Carino to explain his current thinking about AI and inequality. He says the tech could bring productivity gains, but they might not benefit everyone.

Simon Johnson, Nobel-winning economist, joined Marketplace's Meghan McCarty Carino to explain his current thinking about AI and inequality. He says the tech could bring productivity gains, but they might not benefit everyone.

As the Trump administration reshapes how federal dollars flow to universities, reform-minded academics are rethinking how to fix the systemic problems on campus without jeopardizing important research.Simon Johnson, professor of entrepreneurship at MIT Sloan School of Management and Nobel Laureate in Economics, joins Oren to unpack why our nation's bloated and bureaucratic universities need reform and how smarter use of federal funding can incentivize it. Plus, the two make sense of how to create new innovation clusters at universities nationwide rather than just at elite coastal institutions.

Government. The Big G. We like to imagine the free market and the invisible hand as being independent from political influence. But Nobel laureate, Simon Johnson, says that influence has been there since the birth of economics. Call it political economy. Call it government and business. Call it our big topic each Wednesday through Labor Day. We're kicking off another semester of Planet Money Summer School asking the biggest question: Why are some nations rich and others poor? With stories from India, New York City and Peru, we look at the ways in which government bureaucracy can help make or break an economy. Tickets for Planet Money Live at the Bell House available here. Planet Money+ supporters get a 10 percent discount off their tickets. Go to plus.npr.org to sign up, if you haven't already, and listen to the July 8th bonus episode to get the discount code.Always free at these links: Apple Podcasts, Spotify, the NPR app or anywhere you get podcasts.Find more Planet Money: Facebook / Instagram / TikTok / Our weekly Newsletter.Planet Money+ supporters get early access to new episodes of Summer School this season! You also get sponsor-free listening, regular bonus episodes, and you'll help support the work of Planet Money. Sign up for Planet Money+ in Apple Podcasts or at plus.npr.org/planetmoney. Learn more about sponsor message choices: podcastchoices.com/adchoicesNPR Privacy Policy

Government. The Big G. We like to imagine the free market and the invisible hand as being independent from political influence. But Nobel laureate, Simon Johnson, says that influence has been there since the birth of economics. Call it political economy. Call it government and business. Call it our big topic each Wednesday through Labor Day. We're kicking off another semester of Planet Money Summer School asking the biggest question: Why are some nations rich and others poor? With stories from India, New York City and Peru, we look at the ways in which government bureaucracy can help make or break an economy. Tickets for Planet Money Live at the Bell House available herePlanet Money+ supporters get a 10 percent discount off their tickets. Go to Plus.npr.org to sign up, if you haven't already, and listen to the July 8th bonus episode to get the discount code.The series is hosted by Robert Smith and produced by Eric Mennel. Our project manager is Devin Mellor. This episode was edited by Planet Money Executive Producer Alex Goldmark and fact-checked by Emily Crawford and Sierra Juarez. Engineering by Neal Rausch.Help support Planet Money and hear our bonus episodes by subscribing to Planet Money+ in Apple Podcasts or at plus.npr.org/planetmoney.Always free at these links: Apple Podcasts, Spotify, the NPR app or anywhere you get podcasts.Find more Planet Money: Facebook / Instagram / TikTok / Our weekly Newsletter.Learn more about sponsor message choices: podcastchoices.com/adchoicesNPR Privacy Policy

28 games later...Matt Davies-Adams has got Simon Johnson and Liam Twomey with him to look back on Friday night's 2-1 victory over Palmeiras. The Athletic's Senior Data Analyst Mark Carey was in Philadelphia for the game and sends us his thoughts - before we take a closer look at Cole Palmer's return to the scoresheet, the hugely impressive debut of João Pedro who was literally just on the beach a few days earlier - and a look at how Andrey Santos faired after his late call up to the starting XI.So, next up it's the Blues' third meeting with a Brazilian side in the tournament as they take on Thiago Silva's Fluminense at MetLife Stadium in New Jersey. We look ahead to the game and ponder whether Nicolas Jackson will be left out in the cold again?Finally, we've got the latest transfer news with Jamie Gittens officially announced as a Chelsea player - plus the latest on Noni Madueke's potential departure to Arsenal... We'll be back on Thursday to look back at the semi-final showdown with Fluminense... and look ahead to Sunday's final?! HOST: Matt Davies-Adams WITH: Liam Twomey, Simon Johnson and Mark Carey PRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

"With the great power to invent technology comes a great responsibility." – In this lively and energetic podcast conversation, economic sciences laureate Simon Johnson talks about how the past, future and present are interconnected, as well as how science fiction and history are intertwined. He comes to the conclusion that “science fiction is history in reverse or history is science fiction in reverse, whichever way you want to think about it. He also tells us about his family history and how his family was part of the steel industry in Sheffield, England. The industrial revolution is discussed as well as the responsibility that comes with inventing technology. Through their lives and work, failures and successes – get to know the individuals who have been awarded the Nobel Prize on the Nobel Prize Conversations podcast. Find it on Acast, or wherever you listen to pods. https://linktr.ee/NobelPrizeConversations© Nobel Prize Outreach. Hosted on Acast. See acast.com/privacy for more information.

We hope no one had any plans on Sunday morning...Matt Davies-Adams has got The Athletic's Luke Bosher and Simon Johnson alongside him to look back on the bonkers 4-1 (AET) victory over Benfica in a crazy match that lasted more than four hours and included a near two-hour delay due to extreme weather.We discuss the pretty farcical scenes in Charlotte which the Blues boss labelled a 'joke', the wonderful resurgence of Reece James who looks well and truly back to his best - and we salute Christopher Nkunku's contribution - even if he still looks set to leave the club after the tournament! Elsewhere, there have been some eye-catching transfer developments with the news that João Pedro and Jamie Gittens look to officially be on their way to Stamford Bridge. What do those signings mean for the current crop of attacking talent and what will they bring to Enzo Maresca's side?We'll be back on Thursday to look ahead to the last eight showdown with Palmeiras in the early hours of Saturday morning in the UK!HOST: Matt Davies-AdamsWITH: Luke Bosher and Simon JohnsonPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

We didn't want to go to Miami anyway...Matt Davies-Adams has got The Athletic's Chelsea experts Liam Twomey and Simon Johnson alongside him to look back on the 3-1 defeat by Flamengo in Philadelphia which means there's work to do if they want to progress to the knockout stages of the Club World Cup.We talk Nicolas Jackson's red, more confusing selection and tactical decisions, Cole Palmer's struggles and whether we should be cutting this group more slack given the circumstances...So it's a shootout for second place in the group on Tuesday night in Philly as Enzo Maresca's side take on Es Tunis. What can we expect from them - and what do we want to see from Chelsea as they look to bounce back from Friday's disappointment? Elsewhere, we react to the news that Mykhailo Mudryk has been charged by the FA with violating its anti-doping rules - and could now face up to a four-year ban.We'll be back on Thursday to discuss all the fallout from the ES Tunis game - and hope that the Blues have set up a round of 16 tie to look forward to on Saturday night!HOST: Matt Davies-AdamsWITH: Simon Johnson and Liam TwomeyPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Jimbo is joined by Jack Lang, Tom Williams, Colin Millar and more in the final week of the domestic season.Chelsea make it a wonderful week and a successful season by adding the Conference League trophy to Champions League qualification. How good are Maresca's Blues? And what happened to Antony?The Champions League final has the panel, and Michael Cox, very excited. Do Inter have all the attacking tools to end PSG's hopes of a first ever European Cup?Carlo Ancelotti is finally unveiled as Brazil manager. Hear more about his squad selection and the mess he's walking into.Plus is Cristiano Ronaldo about to sham his way into the Club World Cup?Produced by Charlie Jones.RUNNING ORDER: • PART 1: Chelsea win the Conference League with Simon Johnson (02.30)• PART 2: Ancelotti arrives in Brazil (25.00) • PART 3: Champions League final preview with Michael Cox (31.00)• PART 4: Ronaldo moving, Earps retiring (40.00) Hosted on Acast. See acast.com/privacy for more information.

We've won it all...Matt Davies-Adams, Simon Johnson and Luke Bosher assemble to celebrate Chelsea's Europa Conference League triumph as they came from a goal down to beat Real Betis 4-1 in Wrocław!We talk through the dramatic evening in Poland including eyebrow-raising team news, a tumultuous first 45 minutes, a sprinkling of Palmer magic and an emphatic comeback.What will this trophy mean for the club going forward? How big a show of character was the second half performance? And how much of a success has Enzo Maresca's first season in charge been?We also react to the breaking news that it looks like Liam Delap could be on his way to Stamford Bridge...We'll be back next week for a more considered look at the 2024-25 campaign as a whole - and look ahead to the impending Club World Cup!HOST: Matt Davies-AdamsWITH: Luke Bosher and Simon JohnsonPRODUCER: Lucy Oliva----------------*Have your say and let us know what you think of the pod!* https://forms.gle/JpkvkcBtSAin92KL8 Hosted on Acast. See acast.com/privacy for more information.

It all comes down to this...Matt Davies-Adams has got Simon Johnson and Luke Bosher alongside him to look ahead to the final day of the Premier League season aka Nottingham Forest (A) aka the MDA Derby to end all MDA Derbies.The Athletic's Nick Miller - who happens to be a Forest fan - stops by to give us an insight into what the Blues should expect from the hosts at the City Ground - who still harbour hopes of nabbing a Champions League spot should they win and results elsewhere go their way.So, what are Chelsea's chances of getting the win? Who will Enzo Maresca trust up top? And what are the ramifications if they fall short? Plus, we've got a quick look ahead to next week's Conference League final, following the midweek pre-match media day which saw the boss express his frustration at the scheduling and confirm that Filip Jörgensen WILL start in goal.And of course - we've got a quiz with a Forest flavour.We'll be back on Monday to hopefully be celebrating Chelsea's safe passage into next season's Champions League AND a look ahead to Wednesday's final.HOST: Matt Davies-AdamsWITH: Luke Bosher, Simon Johnson and Nick MillerPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

It was never going to be pretty, was it?!Matt Davies-Adams has got The Athletic's Chelsea experts Liam Twomey and Simon Johnson alongside him to look back on the narrow 1-0 victory over Manchester United in the Premier League on Friday night.We talk Marc Cucurella's incredible hot streak in front of goal, the invaluable contribution of Reece James which is making team selection difficult for Enzo Maresca - and the changing mood around the club and in the boardroom following the final home game of the season. Then it's off to Wembley - where CFCW wrapped up their remarkable domestic campaign in style by completing the treble in a comprehensive 3-0 victory over Man United. We'll be back on Thursday to look ahead to the MDA Derby to end all MDA Derbies... yikes!HOST: Matt Davies-AdamsWITH: Liam Twomey and Simon JohnsonPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

On Sunday afternoon Trent Alexander-Arnold was booed at Anfield. So why do supporters boo their own players and is it ever acceptable?Host: Ayo AkinwolereWith: James Pearce, Oli Kay, Carl AnkaFeaturing: Art de Roché, Simon Johnson, Chris WaughExecutive Producer: Adey MoorheadProducers: Guy Clarke and Jay Beale Hosted on Acast. See acast.com/privacy for more information.

Oh, Nicholas...Matt Davies-Adams is joined by The Athletic's Liam Twomey and Luke Bosher to run the rule over Sunday's 2-0 defeat at Newcastle.There's only one place to start (unfortunately) - we get the post-match thoughts of Simon Johnson from the St. James' Park press box and hear him in conversation with Enzo Maresca following the 36th-minute red card handed out to Nicholas Jackson after his senseless forearm smash on Sven Botman.We touch on the lack of intensity from the very first minute, the tactical naivety of the side which seemed to have been found out by Eddie Howe - and what this means for hopes of securing a top five finish with just Manchester United and Nottingham Forest to come in the Premier League.As is almost always the case, CFCW provided some joy as they wrapped up a historic unbeaten WSL season in their last-gasp 1-0 win over Liverpool at Stamford Bridge!We'll be back at the slightly earlier time of Wednesday to look ahead to Friday night's really, really must-win game against hapless Manchester United at the Bridge - and we'll preview Sunday's Women's FA Cup Final at Wembley.HOST: Matt Davies-AdamsWITH: Luke Bosher, Liam Twomey and Simon JohnsonPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

The most low-key semi-final second leg ever?!Matt Davies-Adams has got The Athletic's Simon Johnson and Luke Bosher alongside him to run the rule over Thursday night's 1-0 victory over Djurgården.It's a result that sealed a 5-1 aggregate victory as the Blues cruised into the Conference League final - where they'll face Real Betis in what's surely going to be a far more competitive contest on the 28th of May.We round up events at Stamford Bridge - and the shocking number of away fans in the home stands - before looking ahead to Sunday afternoon's top five showdown at Newcastle United.Plus, Chelsea Women look go complete an undefeated WSL season when they host Liverpool at the Bridge on the final day of the campaign!We'll be back on Monday to look back on all the action across the weekend - with CFCW looking to go unbeaten and CFC looking to take a huge step towards locking in a top five finish.HOST: Matt Davies-AdamsWITH: Luke Bosher and Simon JohnsonPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Where would Chelsea be in the table if Romeo Lavia had been fit all season?!Matt Davies-Adams has The Athletic's Simon Johnson and Liam Twomey alongside him to look back on the huge 3-1 victory over Liverpool at Stamford Bridge on Sunday. We talk Cole Palmer's masterful performance, Romeo Lavia's pivotal role which as been sorely missed too often in this campaign - and the tireless work of Moises Caicedo as the three points helped Enzo Maresca's side move a step closer to Champions League football next season. We celebrate the winners at the end of season awards, look ahead to Thursday night's second leg against Djurgården which the Blues take a commanding lead into - and shoutout CFCW who got a guard of honour AND a win at Tottenham for good measure.We'll be back on Friday to hope that the men have put in a better performance than the last Conference League return leg... and look ahead to another massive game with the trip to Brentford on the horizon! HOST: Matt Davies-Adams WITH: Simon Johnson and Liam Twomey PRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Where would Chelsea be in the table if Romeo Lavia had been fit all season?! Matt Davies-Adams has The Athletic's Simon Johnson and Liam Twomey alongside him to look back on the huge 3-1 victory over Liverpool at Stamford Bridge on Sunday. We talk Cole Palmer's masterful performance, Romeo Lavia's pivotal role which as been sorely missed too often in this campaign - and the tireless work of Moises Caicedo as the three points helped Enzo Maresca's side move a step closer to Champions League football next season. We celebrate the winners at the end of season awards, look ahead to Thursday night's second leg against Djurgården which the Blues take a commanding lead into - and shoutout CFCW who got a guard of honour AND a win at Tottenham for good measure. We'll be back on Friday to hope that the men have put in a better performance than the last Conference League return leg... and look ahead to another massive game with the trip to Brentford on the horizon! HOST: Matt Davies-Adams WITH: Simon Johnson and Liam Twomey PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

First came Didier, then came Romelu, then came...Matt Davies-Adams has got Dom Fifield and the returning Super Sammy Parkin alongside him to look back on the comprehensive 4-1 Conference League semi-final first leg victory over Djurgården. Simon Johnson spoke to us at full-time to give a flavour of events on the ground in Sweden.Then our focus shifts back to the Premier League and the visit of Liverpool to Stamford Bridge on Sunday. We might be subjected to a guard of honour - but can Chelsea get the better of the champions and take another huge step towards securing Champions League football next season?There's jubilation for CFCW who wrapped up their sixth straight WSL title on Wednesday night with the 1-0 victory at Manchester United. The Athletic's Megan Feringa is back with her assessment of how big an achievement it is in Sonia Bompastor's first season in charge. We've got a pretty mouthwatering quiz with Sam looking to reclaim his old crown as the most fearsome competitor of all.Plus, we pay our tributes to a man who was the definition of 'Proper Chels' following the incredibly sad news of Paul Lagan's passing. We'll be back on Monday to reflect on the visit of Liverpool and look ahead to the second leg against Djurgården on Thursday night.HOST: Matt Davies-AdamsWITH: Dom Fifield, Simon Johnson, Megan Feringa and Sam ParkinPRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

First came Didier, then came Romelu, then came...Matt Davies-Adams has got Dom Fifield and the returning Super Sammy Parkin alongside him to look back on the comprehensive 4-1 Conference League semi-final first leg victory over Djurgården. Simon Johnson spoke to us at full-time to give a flavour of events on the ground in Sweden.Then our focus shifts back to the Premier League and the visit of Liverpool to Stamford Bridge on Sunday. We might be subjected to a guard of honour - but can Chelsea get the better of the champions and take another huge step towards securing Champions League football next season?There's jubilation for CFCW who wrapped up their sixth straight WSL title on Wednesday night with the 1-0 victory at Manchester United. The Athletic's Megan Feringa is back with her assessment of how big an achievement it is in Sonia Bompastor's first season in charge.We've got a pretty mouthwatering quiz with Sam looking to reclaim his old crown as the most fearsome competitor of all.Plus, we pay our tributes to a man who was the definition of 'Proper Chels' following the incredibly sad news of Paul Lagan's passing.We'll be back on Monday to reflect on the visit of Liverpool and look ahead to the second leg against Djurgården on Thursday night.HOST: Matt Davies-AdamsWITH: Dom Fifield, Simon Johnson, Megan Feringa and Sam ParkinPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Does your Djurgården need watering? Matt Davies-Adams is joined by Simon Johnson and Luke Bosher for your Monday dose of Chelsea chat. We begin with a look back on the 1-0 victory over Everton on Saturday - with Jackson back amongst the goals, Lavia back in the starting line up - and Chelsea looking like they're back in with a realistic chance of a top five finish. Then, it's all eyes on the Conference League semi-final first leg, with the Blues on their way out to Djurgården. And finally, there was disappointment at Stamford Bridge as CFCW suffered another battering at the hands of a relentless Barcelona, beaten 4-1 on the day and 8-2 (yikes) on aggregate. The Athletic's Megan Feringa helps us look ahead to what this means for the rest of the season for Sonia Bompastor's side and how they recover. We'll be back on Friday to reflect on the trip to Sweden and look ahead to the visit of champions Liverpool to Stamford Bridge on Sunday afternoon. HOST: Matt Davies-Adams WITH: Luke Bosher and Simon Johnson PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

Does your Djurgården need watering?Matt Davies-Adams is joined by Simon Johnson and Luke Bosher for your Monday dose of Chelsea chat.We begin with a look back on the 1-0 victory over Everton on Saturday - with Jackson back amongst the goals, Lavia back in the starting line up - and Chelsea looking like they're back in with a realistic chance of a top five finish. Then, it's all eyes on the Conference League semi-final first leg, with the Blues on their way out to Djurgården. And finally, there was disappointment at Stamford Bridge as CFCW suffered another battering at the hands of a relentless Barcelona, beaten 4-1 on the day and 8-2 (yikes) on aggregate. The Athletic's Megan Feringa helps us look ahead to what this means for the rest of the season for Sonia Bompastor's side and how they recover. We'll be back on Friday to reflect on the trip to Sweden and look ahead to the visit of champions Liverpool to Stamford Bridge on Sunday afternoon. HOST: Matt Davies-Adams WITH: Luke Bosher and Simon Johnson PRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Now is not the time to get stuck in a spot of bother...Matt Davies-Adams has got The Athletic's Chelsea experts Simon Johnson and Liam Twomey alongside him to look ahead to Saturday's visit of the Toffees at Stamford Bridge.On Sunday Chelsea Women try and pull off the unthinkable and overturn a three-goal deficit against Barcelona in their Champions League semi-final second leg. Megan Feringa gives us her take on their chances of turning the tie on its head.Plus, what's being done to create a fiercer and more lively atmosphere at Stamford Bridge? Richard and Alex from We Are The Shed join us to explain the steps being put in place to try and make the Bridge a fortress and bring more colour and noise to the Shed End. We'll be back on Monday to look back on the early kick-off against Everton, hope for a CFCW miracle against Barca and look ahead to Thursday's trip to Djurgården in the Conference League.!HOST: Matt Davies-Adams WITH: Simon Johnson and Liam Twomey PRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Now is not the time to get stuck in a spot of bother... Matt Davies-Adams has got The Athletic's Chelsea experts Simon Johnson and Liam Twomey alongside him to look ahead to Saturday's visit of the Toffees at Stamford Bridge. On Sunday Chelsea Women try and pull off the unthinkable and overturn a three-goal deficit against Barcelona in their Champions League semi-final second leg. Megan Feringa gives us her take on their chances of turning the tie on its head. Plus, what's being done to create a fiercer and more lively atmosphere at Stamford Bridge? Richard and Alex from We Are The Shed join us to explain the steps being put in place to try and make the Bridge a fortress and bring more colour and noise to the Shed End. We'll be back on Monday to look back on the early kick-off against Everton, hope for a CFCW miracle against Barca and look ahead to Thursday's trip to Djurgården in the Conference League.! HOST: Matt Davies-Adams WITH: Simon Johnson and Liam Twomey PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

Has a team ever reached a European semi-final but been booed off the pitch? Asking for a friend...Matt Davies-Adams, Luke Bosher and Dom Fifield unite BEFORE the Legia game to look ahead to Sunday's visit to Fulham in the Premier League. But don't worry - thanks to the magic of editing we also hear from Simon Johnson in the press box after the hugely demoralising 2-1 defeat by Legia Warsaw in the Conference League which threw up more questions than answers. We look ahead to the small matter of a Champions League semi-final first leg over in Barcelona for CFCW, talk agents fees and veteran strikers and hear from Pat Harding - son of Matthew - who's following in his father's footsteps after becoming chairman of Hassocks FC. HOST: Matt Davies-Adams WITH: Luke Bosher, Dom Fifield and Simon Johnson PRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Has a team ever reached a European semi-final but been booed off the pitch? Asking for a friend... Matt Davies-Adams, Luke Bosher and Dom Fifield unite BEFORE the Legia game to look ahead to Sunday's visit to Fulham in the Premier League. But don't worry - thanks to the magic of editing we also hear from Simon Johnson in the press box after the hugely demoralising 2-1 defeat by Legia Warsaw in the Conference League which threw up more questions than answers. We look ahead to the small matter of a Champions League semi-final first leg over in Barcelona for CFCW, talk agents fees and veteran strikers and hear from Pat Harding - son of Matthew - who's following in his father's footsteps after becoming chairman of Hassocks FC. HOST: Matt Davies-Adams WITH: Luke Bosher, Dom Fifield and Simon Johnson PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

What is it about Ipswich?!Matt Davies-Adams has got Luke Bosher and Simon Johnson alongside him to mull over the pretty disastrous 2-2 draw with the Tractor Boys at Stamford Bridge.We touch on the fractious relationship between Enzo Maresca and the fans after his pointed post-match comments, the lack of leadership amongst the squad and the costliness of the back-to-back draws with a pretty treacherous run-in to come. Then it's onto Thursday's visit of Legia in the Conference League quarter-final second leg. The Blues take a 3-0 advantage into the tie... surely they can't mess that up!?Plus, there was late drama for CFCW as Aggie Beever-Jones scored a 94th minute winner as Chelsea beat Liverpool 2-1 to book their place in the FA Cup final!We'll be back on Friday to round up the Thursday night's European escapades and look ahead to the tricky trip just down the road to take on Fulham in the Premier League on Sunday. HOST: Matt Davies-Adams WITH: Luke Bosher and Simon Johnson PRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

What is it about Ipswich?! Matt Davies-Adams has got Luke Bosher and Simon Johnson alongside him to mull over the pretty disastrous 2-2 draw with the Tractor Boys at Stamford Bridge. We touch on the fractious relationship between Enzo Maresca and the fans after his pointed post-match comments, the lack of leadership amongst the squad and the costliness of the back-to-back draws with a pretty treacherous run-in to come. Then it's onto Thursday's visit of Legia in the Conference League quarter-final second leg. The Blues take a 3-0 advantage into the tie... surely they can't mess that up!? Plus, there was late drama for CFCW as Aggie Beever-Jones scored a 94th minute winner as Chelsea beat Liverpool 2-1 to book their place in the FA Cup final! We'll be back on Friday to round up the Thursday night's European escapades and look ahead to the tricky trip just down the road to take on Fulham in the Premier League on Sunday. HOST: Matt Davies-Adams WITH: Luke Bosher and Simon Johnson PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

President Trump stunned many by pausing higher tariff rates on most other countries for 90 days. But the president raised tariffs on Chinese imports to 125 percent after Beijing retaliated overnight. This led to a historic day of rallies in the markets after multiple days of steep drops. Lisa Desjardins reports and Amna Nawaz discusses more with economists Simon Johnson and Douglas Irwin. PBS News is supported by - https://www.pbs.org/newshour/about/funders

Poor old Ange...Matt Davies-Adams has got The Athletic's Simon Johnson and Luke Bosher in tow to look back on the fiery and thoroughly deserved 1-0 victory over Tottenham at Stamford Bridge on Thursday night.We talk the triumphant return of Nicholas Jackson, Caicedo's extraordinary engine and the much-improved showing from the Blues, buoyed on by a raucous crowd. Now - can they translate that home form to Sunday's away day at Brentford?! Enzo Maresca's side are hoping to avoid suffering five straight Premier League defeats on the road when they face the Bees. We'll be back on Monday to reflect on the short trip to the Gtech and preview Thursday's Conference League quarterfinal first leg in Poland! HOST: Matt Davies-Adams WITH: Luke Bosher and Simon Johnson PRODUCER: Lucy OlivaWe're asking you to fill out a quick survey about you and your podcast habits by going to theathletic.com/athletic/survey25. Three lucky entries will win £/$100 worth of Amazon vouchers too. Hosted on Acast. See acast.com/privacy for more information.

Poor old Ange... Matt Davies-Adams has got The Athletic's Simon Johnson and Luke Bosher in tow to look back on the fiery and thoroughly deserved 1-0 victory over Tottenham at Stamford Bridge on Thursday night. We talk the triumphant return of Nicholas Jackson, Caicedo's extraordinary engine and the much-improved showing from the Blues, buoyed on by a raucous crowd. Now - can they translate that home form to Sunday's away day at Brentford?! Enzo Maresca's side are hoping to avoid suffering five straight Premier League defeats on the road when they face the Bees. We'll be back on Monday to reflect on the short trip to the Gtech and preview Thursday's Conference League quarterfinal first leg in Poland! HOST: Matt Davies-Adams WITH: Luke Bosher and Simon Johnson PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

Matt Davies-Adams is joined by Liam Twomey and Luke Bosher to get back up to speed with all things Chelsea Football Club after the international break. We begin with a round up of the latest Blues news since we've been off - including more stadium uncertainty, a new wonderkid and a revoked day off...We've got a special guest, as club legend John Terry speaks to Simon Johnson to commemorate the 20th anniversary of THAT remarkable defence that conceded just 15 goals in 38 Premier League games in their record-breaking first title charge under Jose Mourinho in 2004-2005. Then, Jessy Parker Humphreys does their best to round up a pretty crazy fortnight in the world of CFCW as they booked their place in the semi-finals of the Champions League in dramatic circumstances.On Thursday it's all eyes on the Premier League as Spurs make the short trip across town to Stamford Bridge. We preview that game and it's importance for Enzo Maresca as the run-in to the end of the season begins in earnest. We'll be back on Friday to run the rule over the visit of Tottenham and look ahead to the trip to Brentford!HOST: Matt Davies-Adams WITH: Luke Bosher, Liam Twomey and Jessy Parker Humphreys PRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

Matt Davies-Adams is joined by Liam Twomey and Luke Bosher to get back up to speed with all things Chelsea Football Club after the international break. We begin with a round up of the latest Blues news since we've been off - including more stadium uncertainty, a new wonderkid and a revoked day off... We've got a special guest, as club legend John Terry speaks to Simon Johnson to commemorate the 20th anniversary of THAT remarkable defence that conceded just 15 goals in 38 Premier League games in their record-breaking first title charge under Jose Mourinho in 2004-2005. Then, Jessy Parker Humphreys does their best to round up a pretty crazy fortnight in the world of CFCW as they booked their place in the semi-finals of the Champions League in dramatic circumstances. On Thursday it's all eyes on the Premier League as Spurs make the short trip across town to Stamford Bridge. We preview that game and it's importance for Enzo Maresca as the run-in to the end of the season begins in earnest. We'll be back on Friday to run the rule over the visit of Tottenham and look ahead to the trip to Brentford! HOST: Matt Davies-Adams WITH: Luke Bosher, Liam Twomey and Jessy Parker Humphreys PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

On the 10th of March, Chelsea Football Club celebrated its 120th anniversary. It's fair to say from 1905 to 2025 there's been chaos, controversy, jubilation, heartache, success, failure and everything in between.   On this episode, we follow the club into the modern day and discuss the seismic changes that have taken place behind the scenes since the takeover by BlueCo in 2022.  Matt Davies-Adams has got Simon Johnson and Liam Twomey alongside him to analyse the current state of the men's team - which it's fair to say is going through a bit of a tumultuous time!  Then, we're joined by The Athletic's Dan Sheldon, who's recently investigated some of the concerns around the ‘CFC LDN' rebrand and whether there are wider connotations…  We had to finish on a high note, so Jessy Parker Humphreys is with us to explain how despite it all - the women's team have maintained their standards of excellence (Man City 1st leg aside!) and continued to win trophies while the men's team have struggled to compete.  Read Simon's piece on Chelsea's rich history before 2003 Read Liam's piece on Chelsea's most important match from each decade Back on Monday to look ahead to the return to Premier League action with the small matter of Tottenham coming to Stamford Bridge - plus we'll check in on the fortunes of CFCW! HOST: Matt Davies-Adams WITH: Simon Johnson, Liam Twomey, Dan Sheldon and Jessy Parker Humphreys PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices

On the 10th of March, Chelsea Football Club celebrated its 120th anniversary. It's fair to say from 1905 to 2025 there's been chaos, controversy, jubilation, heartache, success, failure and everything in between.  On this episode, we follow the club into the modern day and discuss the seismic changes that have taken place behind the scenes since the takeover by BlueCo in 2022. Matt Davies-Adams has got Simon Johnson and Liam Twomey alongside him to analyse the current state of the men's team - which it's fair to say is going through a bit of a tumultuous time! Then, we're joined by The Athletic's Dan Sheldon, who's recently investigated some of the concerns around the ‘CFC LDN' rebrand and whether there are wider connotations… We had to finish on a high note, so Jessy Parker Humphreys is with us to explain how despite it all - the women's team have maintained their standards of excellence (Man City 1st leg aside!) and continued to win trophies while the men's team have struggled to compete. Read Simon's piece on Chelsea's rich history before 2003 Read Liam's piece on Chelsea's most important match from each decadeBack on Monday to look ahead to the return to Premier League action with the small matter of Tottenham coming to Stamford Bridge - plus we'll check in on the fortunes of CFCW!HOST: Matt Davies-AdamsWITH: Simon Johnson, Liam Twomey, Dan Sheldon and Jessy Parker HumphreysPRODUCER: Lucy Oliva Hosted on Acast. See acast.com/privacy for more information.

On the 10th of March, Chelsea Football Club celebrated its 120th anniversary. It's fair to say from 1905 to 2025 there's been chaos, controversy, jubilation, heartache, success, failure and everything in between.   On this episode, we go back to July 1st, 2003 - and the day the course of the club's history changed forever when Roman Abramovich became owner. Matt Davies-Adams has got The Athletic's Dom Fifield and Simon Johnson alongside him to reminisce about the glory days, the José years - and the experience of covering the club during that period.  And what was it like to be a fan growing up in that era? Younger fans are often tarred with a glory hunter brush, but Luke Bosher explains what it was like to be introduced to the club when they were serial winners and at the height of their powers.  Plus, Liam Twomey's back to help us finish off our overview of the defining fixtures from each decade, from the 1980s through to the modern day.  Read Simon's piece on Chelsea's rich history before 2003 Read Liam's piece on Chelsea's most important match from each decade HOST: Matt Davies-Adams WITH: Simon Johnson, Liam Twomey, Luke Bosher & Dom Fifield  PRODUCER: Lucy Oliva Learn more about your ad choices. Visit megaphone.fm/adchoices